2006ǯ4·î23Æü(Æü) | 18:00¡Á20:00 |
2006ǯ4·î24Æü(·î) | 8:00¡Á |
2006ǯ4·î25Æü(²Ð) | 8:00¡Á |
2006ǯ4·î24Æü(·î) [²ñ¾ì: ·Ú°æÂô¥×¥ê¥ó¥¹¥Û¥Æ¥ë¡¦À¾´Û¡¦¹ñºÝ²ñµÄ¾ì Àõ´Ö] |
A | Ba | Bd | C | D |
---|---|---|---|---|
VLSI¤Î¥Î¥¤¥º¡¦¥¿¥¤¥ß¥ó¥°²òÀÏ |
ADÊÑ´¹²óÏ© |
ÈóÀþ·Á¡¦Å¬±þ¿®¹æ½èÍý |
Àß·×»öÎã |
|
²óÏ©¤È¥·¥¹¥Æ¥à¤ÎÍýÏÀ |
RF¥·¥¹¥Æ¥à |
±ÇÁü¿®¹æ½èÍý |
ÄÌ¿®¤È¹çÀ®¼êË¡ |
·Á¼°Åª¼êË¡ |
¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¥ï¡¼¥¯ |
[ÆÃÊÌ¥»¥Ã¥·¥ç¥ó]̤Íè¼Ò²ñ¤ò¼Â¸½¤¹¤ë¥»¥ó¥µ²óÏ©µ»½Ñ1 |
²èÁü½èÍý¡ÊÉü¸µ¡¦¶¯Ä´¡Ë |
¥Õ¥í¥¢¥×¥é¥ó |
[ÆÃÊÌ¥»¥Ã¥·¥ç¥ó]¿·À¤Âå¤Î·×»»¸Â³¦I |
[ÆÃÊÌ¥»¥Ã¥·¥ç¥ó]ÀèüMOS¥â¥Ç¥ë¤ÎÆ°¸þ |
[ÆÃÊÌ¥»¥Ã¥·¥ç¥ó]̤Íè¼Ò²ñ¤ò¼Â¸½¤¹¤ë¥»¥ó¥µ²óÏ©µ»½Ñ2 |
[ÆÃÊÌ¥»¥Ã¥·¥ç¥ó]±ÇÁü¡¦²»¶Á¿®¹æ½èÍý¤Î¾ÍèŸ˾¤È²ÝÂê |
¥ì¥¤¥¢¥¦¥È¥¢¥ë¥´¥ê¥º¥à |
[ÆÃÊÌ¥»¥Ã¥·¥ç¥ó]¿·À¤Âå¤Î·×»»¸Â³¦II |
[ÆÃÊÌ¥»¥Ã¥·¥ç¥ó]VDEC |
||||
¾©Îå¾Þɽ¾´¼° 17:30-17:40 [²ñ¾ì: ĹÌî] | ||||
ÆÃÊ̾·ÂÔ¹Ö±é: ¡Ö¡Ö²ÁÃ͡פȡֿ®Íѡפò¼è¤ê°·¤¦¾ðÊ󵻽Ѥ˸þ¤±¤Æ¡× °Â±º ´²¿Í(¶å½£Âç³Ø) 17:40-18:40 [²ñ¾ì: ĹÌî] | ||||
º©¿Æ²ñ 18:40-20:40 [²ñ¾ì: ĹÌî] |
2006ǯ4·î25Æü(²Ð) [²ñ¾ì: ·Ú°æÂô¥×¥ê¥ó¥¹¥Û¥Æ¥ë¡¦À¾´Û¡¦¹ñºÝ²ñµÄ¾ì Àõ´Ö] |
A | Ba | Bd | C | D |
---|---|---|---|---|
¿®¹æÅÁÁ÷²óÏ© |
¥Õ¥£¥ë¥¿ |
DFM |
¥Í¥Ã¥È¥ï¡¼¥¯¤Î¿®ÍêÀ |
|
[ÆÃÊÌ¥»¥Ã¥·¥ç¥ó]¥¹¥¤¥Ã¥Á¥ó¥°·Ï¤Î¥À¥¤¥Ê¥ß¥¯¥¹¤È¥Ï¥¤¥Ö¥ê¥Ã¥ÉÀ |
ÅŸ»²óÏ© |
´ðÁᦲ»¶Á¿®¹æ½èÍý |
[ÆÃÊÌ¥»¥Ã¥·¥ç¥ó]DFM |
[ÆÃÊÌ¥»¥Ã¥·¥ç¥ó]¥â¥Ç¥ë¸¡ºº¤Î±þÍÑ |
[An/Dʬ²Ê²ñ¹çƱÆÃÊÌ¥»¥Ã¥·¥ç¥ó]¥Ï¥¤¥Ö¥ê¥Ã¥É¥À¥¤¥Ê¥ß¥«¥ë¥·¥¹¥Æ¥à |
¦¤¦²AD/DAÊÑ´¹²óÏ© |
²èÁü±þÍÑ |
¥ê¥³¥ó¥Õ¥£¥®¥ã¥é¥Ö¥ë¤È¥¥ã¥Ã¥·¥åºÇŬ²½ |
|
¥Ë¥å¡¼¥í¥À¥¤¥Ê¥ß¥¯¥¹ |
¥¢¥Ê¥í¥°Í×ÁDzóÏ© |
²èÁüǧ¼± |
¹â°ÌÀß·× |
¥°¥é¥Õ¥¢¥ë¥´¥ê¥º¥à |
Âê̾ | Calculating the Effective Capacitance for Interconnect Loads Based on Thevenin Model |
Ãø¼Ô | ¡ûShuai Fang, Zhangcai Huang(Waseda University), Atsushi Kurokawa(Semiconductor Technology Academic Research Center), Yasuaki Inoue(Waseda University) |
Page | pp. 1 - 4 |
Keyword | Effective Capacitance, Interconnect Loads, CMOS Gates, Thevenin Model |
Abstract | Interconnect wires give large influences on circuit delay in very deep submicron designs. Thevenin model and effective capacitance Ceff concept are usually used to calculate the delay of gate with interconnect loads. In the researches before, the condition that the charges transferred to Ceff and RC-pi are not equal was not considered. With the progress of IC process technology, its influence on Static Timing Analysis becomes larger. In this paper, we consider this condition, and propose an new algorithm for calculating the effective capacitance based on Thevenin model. Experimental results show that it is in agreement with the Spice simulation. |
Âê̾ | LSI ÇÛÀþ¤Ë¤ª¤±¤ëÍÆÎÌÀ, ͶƳÀ¥¯¥í¥¹¥È¡¼¥¯¥Î¥¤¥º¤ÎÄêÎÌŪ¾Íèͽ¬ |
Ãø¼Ô | ¡û¾®³Þ¸¶ ÂÙ¹°, ¶¶ËÜ ¾»µ¹, Èø¾å ¹§Íº(ÂçºåÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê¾ðÊó¥·¥¹¥Æ¥à¹©³ØÀ칶) |
Page | pp. 5 - 10 |
Keyword | ÍÆÎÌÀ¥¯¥í¥¹¥È¡¼¥¯¥Î¥¤¥º, ͶƳÀ¥¯¥í¥¹¥È¡¼¥¯¥Î¥¤¥º, ÇÛÀþ¥¹¥±¡¼¥ê¥ó¥° |
Abstract | ÍÆÎÌÀ¥¯¥í¥¹¥È¡¼¥¯¥Î¥¤¥º¤Ï½¾Íè¤è¤êÇÛÀþÃÙ±ä¤ÎÊÑÆ°¤ÎÍ×°ø¤È¤·¤ÆÃΤé¤ì, ÇÛÀþ¤Î¥¹¥±¡¼¥ê¥ó¥°¤Ë¤è¤Ã¤Æº£¸å¤è¤ê¿¼¹ï¤Ë¤Ê¤ë¤È¹Í¤¨¤é¤ì¤Æ¤¤¤ë. °ìÊý, Àèü¤Î¥×¥í¥»¥¹¤Î¥°¥í¡¼¥Ð¥ëÇÛÀþ¤Ë¤ª¤¤¤Æ¤Ï¿®¹æ¼þÇÈ¿ô¤Î¾å¾º¤Ë¤è¤Ã¤ÆͶƳÀ¥¯¥í¥¹¥È¡¼¥¯¥Î¥¤¥º¤¬½ÅÍפÊÌäÂê¤È¤Ê¤ê¤Ä¤Ä¤¢¤ë. ËÜÏÀʸ¤Ç¤Ï¾Íè¤Î¥×¥í¥»¥¹¤Ë¤ª¤±¤ëÍÆÎÌÀ, ͶƳÀ¥¯¥í¥¹¥È¡¼¥¯¥Î¥¤¥º¤Î·¹¸þ¤Ë¤Ä¤¤¤ÆÄêÎÌŪ¤Êͽ¬¤ò¹Ô¤¦. ITRS ¤Îͽ¬¤Ë´ð¤Å¤, ¥×¥í¥»¥¹¤Î¿Ê²½¤Ë´Ø¤¹¤ë 2 ¼ï¤Îͽ¬¥·¥Ê¥ê¥ª¤ò²¾Äꤷ¤Æ³Æ¼ï¥Ñ¥é¥á¡¼¥¿¤òÀßÄꤷ, ²óÏ©¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤Ë¤è¤ê¥Î¥¤¥º¿¶Éý, ¥¿¥¤¥ß¥ó¥°¤Ø¤Î±Æ¶Á¤òɾ²Á¤¹¤ë. |
Âê̾ | ÅŸ»¥Î¥¤¥ºµ¯°ø¥¯¥í¥Ã¥¯¥¸¥Ã¥¿¤Î¸«ÀѤê¼êË¡¤ÎÄó°Æ |
Ãø¼Ô | ˪²° ¹§ÂÀϺ, ¡ûÂçÅè ¹§¹¬, ÃæÅç ±ÑÀÆ(NEC¥¨¥ì¥¯¥È¥í¥Ë¥¯¥¹¡Ê³ô¡Ë) |
Page | pp. 11 - 16 |
Keyword | ÅŸ»¥Î¥¤¥º, ¥¯¥í¥Ã¥¯¥¸¥Ã¥¿ |
Abstract | LSIÆâÉô¤Î¥¯¥í¥Ã¥¯¿®¹æ¤Î¥¸¥Ã¥¿¤Î¤¦¤Á¡¤ÅŸ»¥Î¥¤¥º¤Ë¤è¤Ã¤Æ¥¯¥í¥Ã¥¯Ê¬Ç۷Ϥˤª¤¤¤ÆÀ¸¤¸¤ë¥¸¥Ã¥¿¤òÀß·×½é´üÃʳ¬¤ÈÀ߷׸¡¾ÚÃʳ¬¤Ç¸«ÀѤâ¤ë¼êË¡¤òÄó°Æ¤¹¤ë¡¥Àß·×½é´üÃʳ¬¤Ç¤Ï¡¤ÅŸ»·Ï¤Î´Ê°×¥â¥Ç¥ë¤ÈÏÀÍý²óÏ©¤¬¾ÃÈñ¤¹¤ëÅŸ»ÅÅή¤È¤«¤éÅŸ»¥Î¥¤¥ºÇÈ·Á¤ò¸«ÀѤâ¤ê¡¤¤³¤ì¤ò¥¯¥í¥Ã¥¯¥Ñ¥¹ÃÙ±ä¤ÎÊÑÆ°¤ËÊÑ´¹¤¹¤ë¡¥À߷׸¡¾ÚÃʳ¬¤Ç¤Ï¡¢¥Á¥Ã¥×Æâ¤Î¥ì¥¤¥¢¥¦¥È¡¦¥Ç¡¼¥¿¤«¤é¾ÜºÙ¤ÊÅŸ»·Ï¤Î¥â¥Ç¥ë¤òÀ¸À®¤·¤ÆÅŸ»¥Î¥¤¥º²òÀϤò¹Ô¤¤¡¢³Æ¥¯¥í¥Ã¥¯¥É¥é¥¤¥Ð¤Ë¤ª¤±¤ë¼Â¸ústatic IR-drop¤òµá¤á¤Æ¥¸¥Ã¥¿¤¬ºÇÂç¤È¤Ê¤ë¥Ñ¥¹¤ò£±¤ÄÁª¤Ó½Ð¤·¡¢¤³¤Î¥Ñ¥¹¤Î¤ß¤Î¥¸¥Ã¥¿¤òSPICE¤Î²áÅϲòÀϤǵá¤á¤ë¡¥ |
Âê̾ | Àþ·Á¾õÂÖ¶õ´Ö¥·¥¹¥Æ¥à¤Î¥°¥é¥ß¥¢¥ó¤òÊݸ¤¹¤ë¼þÇÈ¿ôÊÑ´¹ |
Ãø¼Ô | ¡û±ÛÅÄ ½Ó²ð , °¤Éô Àµ±Ñ, ÀîËô À¯À¬(ÅìËÌÂç³ØÂç³Ø±¡ ¹©³Ø¸¦µæ²Ê ÅŻҹ©³ØÀ칶) |
Page | pp. 17 - 22 |
Keyword | Àþ·ÁϢ³»þ´Ö¥·¥¹¥Æ¥à, ¾õÂÖ¶õ´Öɽ¸½, ²ÄÀ©¸æÀ¥°¥é¥ß¥¢¥ó, ²Ä´Ñ¬À¥°¥é¥ß¥¢¥ó, ¼þÇÈ¿ôÊÑ´¹ |
Abstract | ¼þÇÈ¿ôÊÑ´¹¤Ï¡¤Àþ·Á²óÏ©Ì֤ˤª¤±¤ë¸Ä¡¹¤Î¥¤¥ó¥À¥¯¥¿¤ª¤è¤Ó¥¥ã¥Ñ¥·¥¿¤òÆÃÄê¤ÎLC²óÏ©ÌÖ¤ÇÃÖ¤´¹¤¨¤ë¤³¤È¤Ë¤è¤ê¡¤Ê̤ÎÆÃÀ¤òͤ¹¤ë¥·¥¹¥Æ¥à¤òÀ¸À®¤¹¤ë¼êË¡¤Ç¤¢¤ë¡¥Ãø¼Ô¤é¤Ï¤³¤ì¤Þ¤Ç¡¤Àþ·ÁϢ³»þ´Ö¥·¥¹¥Æ¥à¤òÂоݤȤ·¤Æ¡¤¾õÂÖ¶õ´Öɽ¸½¤Ë´ð¤Å¤¯¼þÇÈ¿ôÊÑ´¹¤Îµ½ÒË¡¤òƳ½Ð¤·¤Æ¤¤¤ë¡¥ËܹƤǤϡ¤¤³¤Îµ½ÒË¡¤ËÂФ·¤Æ¡¤LC²óÏ©Ì֤ξõÂÖ¶õ´Öɽ¸½¤Ë´Ø¤¹¤ëÀ©Ìó¤ò¿·¤¿¤ËÀߤ±¤ë¤³¤È¤ò¹Í¤¨¤ë¡¥¤½¤·¤Æ¡¤¤³¤ÎÀ©Ìó¤Ë´ð¤Å¤¤¤Æ¼þÇÈ¿ôÊÑ´¹¤Îµ½ÒË¡¤ò½¤Àµ¤·¡¤¤½¤Î·ë²Ì¤È¤·¤Æ¥·¥¹¥Æ¥à¤Î²ÄÀ©¸æÀ¡¦²Ä´Ñ¬À¥°¥é¥ß¥¢¥ó¤¬Êݸ¤µ¤ì¤ë¤è¤¦¤Ê¿·¤·¤¤¼þÇÈ¿ôÊÑ´¹¤Îµ½ÒË¡¤òƳ½Ð¤¹¤ë¡¥¤Þ¤¿¡¤¤³¤Î¿·¤·¤¤µ½ÒË¡¤Ë´ð¤Å¤¤¤ÆÀ¸À®¤µ¤ì¤ë¤µ¤Þ¤¶¤Þ¤Ê¥·¥¹¥Æ¥à¤¬¥°¥é¥ß¥¢¥ó¤Î´ÑÅÀ¤«¤éƱ°ì¤Î¹½Â¤¤òͤ¹¤ë¡¤¤È¤¤¤¦¶½Ì£¿¼¤¤À¼Á¤ò¼¨¤¹¡¥ |
Âê̾ | A Pseudo-Transient Method Using Compound Elements for Finding DC Operating Points |
Ãø¼Ô | ¡ûHong Yu, Yasuaki Inoue, Yuki Matsuya, Zhangcai Huang(Graduate School of Information, Production and Systems, Waseda University) |
Page | pp. 23 - 28 |
Keyword | pesudo-transient analysis, compound element, DC operating point, nonlinear circuit, oscillation |
Abstract | In order to overcome the non-convergence of the Newton-Raphson method in circuit simulation, the pseudo-transient algorithm with the novel compound elements is proposed in this paper. Compared with the conventional pseudo-transient algorithms, the proposed algorithm is proved to be efficient and insensitive to oscillation problems. |
Âê̾ | SPICE¤Ë´Êñ¤Ë¼ÂÁõ¤Ç¤¤ë¸úΨŪ¤Ê¥Û¥â¥È¥Ô¡¼Ë¡ |
Ãø¼Ô | ¡û¹õÌÚ ¾Ä, »³Â¼ À¶Î´(Ãæ±ûÂç³ØÍý¹©³ØÉôÅŵ¤ÅŻҾðÊóÄÌ¿®¹©³Ø²Ê) |
Page | pp. 29 - 34 |
Keyword | ²óÏ©¥·¥ß¥å¥ì¡¼¥·¥ç¥ó, ľή²òÀÏ, ¥Û¥â¥È¥Ô¡¼Ë¡, SPICE, ¥Ñ¥¹ÄÉÀײóÏ© |
Abstract | Âç°èŪ¼ý«À¡ÊǤ°Õ¤Î½é´üÃͤ«¤éɬ¤º²ò¤Ë¼ý«¤¹¤ëÀ¼Á¡Ë¤¬¤¢¤ê¡¤¤«¤ÄÈó¾ï¤Ë¸úΨ¤¬Îɤ¤ÈóÀþ·Á²óÏ©¤Îľή²òÀÏË¡¤È¤·¤Æ²ÄÊÑÍøÆÀ¥Ë¥å¡¼¥È¥ó¥Û¥â¥È¥Ô¡¼Ë¡¤¬Äó°Æ¤µ¤ì¤Æ¤¤¤ë¡¥¤·¤«¤·Â絬ÌϤÇÊ£»¨¤Ê²óÏ©¤Ë¤â¸úΨÎɤ¯Å¬ÍѤǤ¤ë¡È¹âÅ٤ʡɥۥâ¥È¥Ô¡¼Ë¡¤ò¼Â¸½¤·¤è¤¦¤È¤¹¤ë¾ì¹ç¡¤¤«¤Ê¤ê¤ÎÀìÌçŪÃ챤ÈÊ£»¨¤Ê¥×¥í¥°¥é¥ß¥ó¥°¤¬É¬ÍפȤʤ뤿¤á¡¤ÈóÀìÌç²È¤ä½é¿´¼Ô¤Ë¤ÏÉßµï¤Î¹â¤¤ÊýË¡¤Ç¤¢¤Ã¤¿¡¥ËܹƤǤϡ¤¡Ö¹âÅ٤ʲÄÊÑÍøÆÀ¥Ë¥å¡¼¥È¥ó¥Û¥â¥È¥Ô¡¼Ë¡¤ò¡×¡Ö¥Û¥â¥È¥Ô¡¼Ë¡¤Î ¤³¤È¤ò¤è¤¯ÃΤé¤Ê¤¯¤Æ¤â¡×¡ÖÊ£»¨¤Ê¥×¥í¥°¥é¥ß¥ó¥°¤ò¹Ô¤¦¤³¤È¤Ê¤¯¡×¡ÖÍưפˡ×SPICE¤Ë¼ÂÁõ¤¹¤ëÊýË¡¤òÄó°Æ¤¹¤ë¡¥ |
Âê̾ | Behavioral Macromodeling of Analog LSI Implementation for Automobile Intake System |
Ãø¼Ô | ¡ûZhangcai Huang, Yasuaki Inoue, Quan Zhang, Shuai Fang, Yuehu Zhou(Waseda University) |
Page | pp. 35 - 38 |
Keyword | Behavioral Circuit Macromodeling, Analog LSI, Automobile Intake System |
Abstract | Accurate estimating or measuring intake manifold absolute pressure plays an important role for the effective automobile engine control. In order to achieve the real-time estimation of the absolute pressure, the high accuracy and high speed processing ability are required for the automobile engine control system. Therefore, in this paper, an analog LSI method is discussed for the automobile electronic control. Furthermore, a novel behavioral macromodel is proposed for further analog LSI design. |
Âê̾ | A Novel Autoassociation Model based on Entropy Minimization Approach |
Ãø¼Ô | ¡ûMasahiro Nakagawa(Ĺ²¬µ»½Ñ²Ê³ØÂç³Ø) |
Page | pp. 39 - 44 |
Keyword | Entropy, Association, Neural Network, Memory Model, Retrieval |
Abstract | In this paper, an entropy based associative memory model will be proposed and applied to memory retrievals with an orthogonal learning model to compare with the conventional autoassociative model. In the present approach, the updating dynamics will be constructed on the basis of the entropy minimization strategy which may be reduced asymptotically to the above-mentioned autocorrelation dynamics as a special case. From numerical results, it will be found that the presently proposed novel approach realizes the larger memory capacity in comparison with the autocorrelation based dynamics such as associatron according to the higher-order correlation involved in the proposed dynamics. |
Âê̾ | Analysis of the Number of Stimulation Units in Pulse-Driven Star-Coupled LC Oscillators |
Ãø¼Ô | ¡ûSeiichiro Moro, Keisuke Hamamoto(University of Fukui), Tadashi Matsumoto(Fukui University of Technology) |
Page | pp. 45 - 50 |
Keyword | star-coupled oscillators, synchronization, phase patterns, pulse train, stimulation units |
Abstract | The LC oscillators star-coupled by one resistor exhibit N-phase oscillation and we can get (N-1)! stable phase states from the permutation of the phase of each oscillator. Using the relationship between the initial states and the phase patterns, we can use the system as some kinds of the neural networks and the associative memories. In this study, we analyze the scheme of the phase pattern switching and the number of stimulation units needed to derive all the phase patterns in pulse-driven star-coupled LC oscillators. In particular, we claim that we need N-2 stimulation units are needed to derive all the patterns. |
Âê̾ | ÁÐÊý¸þSOM¤òÍѤ¤¤¿É÷¶·Í½Â¬¤Î°ì¼êË¡ |
Ãø¼Ô | ¡ûÆ£¾¾ À¿°ìϺ(Ä»¼è´Ä¶Âç³Ø Âç³Ø±¡ ´Ä¶¾ðÊó³Ø¸¦µæ²Ê), Ïɸ« °éμ(Ä»¼è´Ä¶Âç³Ø ´Ä¶¾ðÊó³ØÉô), ¿¢ÅÄ ÂóÌé(Ä»¼è´Ä¶Âç³Ø Âç³Ø±¡ ´Ä¶¾ðÊó³Ø¸¦µæ²Ê), ¾®ÎÓ ÈôÄ»(Ä»¼è´Ä¶Âç³Ø ´Ä¶¾ðÊó³ØÉô), ÃÛë δͺ(¾¾¹¾¹©¶È¹âÅùÀìÌç³Ø¹»), Éû°æ ͵(Ä»¼èÂç³Ø ¹©³ØÉô) |
Page | pp. 51 - 56 |
Keyword | ¼«¸ÊÁÈ¿¥²½¥Þ¥Ã¥×, É÷¶·Í½Â¬, É÷ÎÏȯÅÅ |
Abstract | ¸½ºß¡¢¿·¥¨¥Í¥ë¥®¡¼¤¬ÃíÌܤµ¤ì¤Æ¤¤¤ë¡£¿·¥¨¥Í¥ë¥®¡¼¤Î°ì¤Ä¤Ç¤¢¤ëÉ÷ÎϤϡ¢¸Ï³é¤Î¿´ÇÛ¤¬¤Ê¤¯Ìµ¿Ô¢¤Ç¤¢¤ê¡¢É÷ÎϤò»È¤Ã¤¿È¯ÅŤÏÆó»À²½ÃºÁǤòÇӽФ·¤Ê¤¤¥¯¥ê¡¼¥ó¤ÊȯÅÅÊýË¡¤È¤·¤Æ¡¢ÆüËܤǤâ°ÂÄꤷ¤¿É÷ÎϤ¬ÆÀ¤é¤ì¤ë±è´ßÉô¤òÃæ¿´¤ËÉ÷ÎÏȯÅŤ¬À¹¤ó¤ËƳÆþ¤µ¤ì¤Æ¤¤¤ë¡£Ïɸ«¸¦µæ¼¼¤Ç¤ÏÄãÉ÷ÎϤǤâȯÅŲÄǽ¤Ê²ÈÄíÍѤξ®·¿È¯Åŵ¡¤ËÃíÌܤ·¤¿¡£É÷ÎÏȯÅŤò´Þ¤à¥·¥¹¥Æ¥à¤ò°ÂÄê¤Ë±¿ÍѤ¹¤ë¤¿¤á¤ËÉ÷¶·¤Îͽ¬¤¬É¬ÍפǤ¢¤ë¤È¹Í¤¨¤Æ¤¤¤ë¡£²æ¡¹¤ÏÏɸ«¸¦µæ¼¼¤Ç¤Ï²ÈÄíÍѤξ®·¿É÷ÎÏȯÅŵ¡¤ò¥¿¡¼¥²¥Ã¥È¤Ë¤·¡¢¶¹°è¤Î¥Ç¡¼¥¿¤òÍѤ¤¤ÆÉ÷®¤Îͽ¬¤ò¹Ô¤Ã¤Æ¤¤¤ë¡£Ëܸ¦µæ¤Ç¤Ï¡¢º£¤Þ¤Ç»ÈÍѤ·¤Æ¤¤¤¿´ðËÜSOM¤ËÂå¤ï¤êÁÐÊý¸þSOM¤ò»ÈÍѤ·É÷®¤òͽ¬¤·¡¢Í½Â¬Î¨¤Î¸þ¾å¤ò¸¡Æ¤¤¹¤ë¡£ |
Âê̾ | (¾·ÂÔ)RFÍÑ MOSFET ¥â¥Ç¥ë HiSIM2 |
Ãø¼Ô | ¡û¹¾ºê ãÌé(¹ÅçÂç³Ø), ¥Ê¥Ð¥í ¥É¥ó¥Ç¥£¡¼, Äç¶á ÎÑÉ×, ÎëÌÚ ³Ø, ÃÝÅÄ ÍÛ°ì, »°Âð Àµ¶Æ, ÏÏÌî ÃÒÇ·, ¿å·ó ÎÉͺ, Ä®ÅÄ ¸², °ð³À μ²ð, ¥Þ¥¿¥¦¥·¥å ¥Ï¥ó¥¹¥æ¥ë¥²¥ó, »°±º Æ»»Ò(¹ÅçÂç³ØÂç³Ø±¡Àèüʪ¼Á²Ê³Ø¸¦µæ²Ê), Âç¹õ ãÌé, ÈÓÄÍ µ®¹°, Åĸý ¾»É§, ·§Âå À®¹§, µÜËÜ ½Ó²ð(ȾƳÂÎÍý¹©³Ø¥»¥ó¥¿¡¼) |
Page | pp. 57 - 62 |
Âê̾ | (¾·ÂÔ)HiSIM¤ÈPSP¤Î¥Ù¥ó¥Á¥Þ¡¼¥¯·ë²Ì |
Ãø¼Ô | ¡ûÂç¹õ ãÌé(³ô¼°²ñ¼ÒÅì¼Ç ¥»¥ß¥³¥ó¥À¥¯¥¿¡¼¼Ò SoC¸¦µæ³«È¯¥»¥ó¥¿¡¼) |
Page | pp. 63 - 67 |
Âê̾ | (¾·ÂÔ)°äÅÁŪ¥¢¥ë¥´¥ê¥º¥à¤òÍѤ¤¤¿SPICE¥â¥Ç¥ë¥Ñ¥é¥á¡¼¥¿¤ÎÃê½Ð¼êË¡¤Î¸¡Æ¤ |
Ãø¼Ô | ¡ûÇÏ¾ì ½ÓÍ´(²Åŵ¤¹©¶È³ô¼°²ñ¼Ò), ¹ÔÊý ½áÌé, ¼À¥ ÂçÊå, ÏÂÅÄ Å¯Åµ(ȾƳÂÎÀèü¥Æ¥¯¥Î¥í¥¸¡¼¥º), °ËÆ£ ·Ë°ì, ¼Àî Àµ¹¨(¿Ê²½¥·¥¹¥Æ¥àÁí¹ç¸¦µæ½ê) |
Page | pp. 69 - 74 |
Keyword | BSIM, GA, SPICE, ¥Ñ¥é¥á¡¼¥¿, Ãê½Ð |
Abstract | Bsim¥â¥Ç¥ë¥Ñ¥é¥á¡¼¥¿¤ÎÃê½Ð¤Ë¤Ï¡¢½¾ÍèLMË¡¤¬ÍѤ¤¤é¤ì¤Æ¤¤¤ë¤¬¡¢¤³¤Î¼êË¡¤Ïû»þ´Ö¤Ë²ò¤òõºº¤¹¤ë¤³¤È¤¬¤Ç¤¤ëÈ¿ÌÌ¡¢Ìµ¼ê½ç¡¦¼«Æ°¥Ñ¥é¥á¡¼¥¿Ãê½Ð¤¬º¤Æñ¤Ç¤¢¤Ã¤¿¡£°ìÊý¡¢¥Ñ¥é¥á¡¼¥¿¤ÎÃê½Ð¤ËGA¤ÎŬÍѤ¹¤ë¾ì¹ç¡¢Â¿¿ô¤Î¥Ñ¥é¥á¡¼¥¿¤òÀ踫Ãμ±Ìµ¤·¤ËÃê½Ð¤Ç¤¤ëÈ¿ÌÌ¡¢Ãê½Ð¤Ë¿¤¯¤Î»þ´Ö¤¬É¬ÍפȤ¤¤¦·çÅÀ¤ò»ý¤Ä¡£ËÜÊó¹ð¤Ç¤Ï¡¢Bsim¥â¥Ç¥ë¥Ñ¥é¥á¡¼¥¿¤ÎÃê½Ð¤ËGA¤òŬÍѤ¹¤ë¾ì¹ç¤Ë¡¢¼ÂÍÑŪ¤Ê»þ´Ö¤ÇÃê½Ð¤¹¤ë¼êË¡¤Ë¤Ä¤¤¤Æ¸¡Æ¤¤·¤¿¡£ |
Âê̾ | ¥¿¥¤¥à¥Ç¥¸¥¿¥¤¥¶¤òÍѤ¤¤¿ÈóƱ´ü¥µ¥ó¥×¥ê¥ó¥°ADÊÑ´¹´ï¤È¿®¹æ½èÍý |
Ãø¼Ô | ¡ûÀ¶¿å °ìÌé, ¸µß· ÆÆ»Ë(·²ÇÏÂç³Ø ¹©³ØÉô Åŵ¤ÅŻҹ©³Ø²Ê ¾®ÎÓ¸¦µæ¼¼), ¾®¼¼ µ®µª(¥¢¥¸¥ì¥ó¥È¡¦¥Æ¥¯¥Î¥í¥¸¡¼¡¦¥¤¥ó¥¿¡¼¥Ê¥·¥ç¥Ê¥ë¡Ê³ô¡ËSOC¥Æ¥¹¥È»ö¶ÈÀ½Éʳ«È¯Éô ), ÎÓ ³¤·³(·²ÇÏÂç³Ø ¹©³ØÉô Åŵ¤ÅŻҹ©³Ø²Ê ¾®ÎÓ¸¦µæ¼¼), ¾®ÎÓ ½ÕÉ× (·²ÇÏÂç³Ø ¹©³ØÉô Åŵ¤ÅŻҹ©³Ø²Ê ¾®ÎÓ¸¦µæ¼¼ ) |
Page | pp. 75 - 80 |
Keyword | ADÊÑ´¹´ï, ¥¿¥¤¥à¥Ç¥¸¥¿¥¤¥¶, ÈóƱ´ü¥µ¥ó¥×¥ê¥ó¥°, Ʊ´ü¥µ¥ó¥×¥ê¥ó¥°, ÈóƱ´üÎ¥»¶¥Õ¡¼¥ê¥¨ÊÑ´¹ |
Abstract | ¤³¤ÎÏÀʸ¤Ç¤Ï¡¢ÈùºÙCMOS¥×¥í¥»¥¹¤Ç¤Î¼Â¸½¤ËŬ¤·¤¿LSI¥Æ¥¹¥¿ÍѤΥ¢¥×¥ê¥±¡¼¥·¥ç¥ó¤È¤·¤Æ¡¢ÈóƱ´ü¥µ¥ó¥×¥ê¥ó¥°ADÊÑ´¹´ï¥¢¡¼¥¥Æ¥¯¥Á¥ã¤òÄó°Æ¤¹¤ë¡£´ð½àÀµ¸¹ÇȤÈÆþÎÏ¿®¹æ¤ò¥³¥ó¥Ñ¥ì¡¼¥¿²óÏ©¤ÇÈæ³Ó¤·¡¢¤½¤Î½ÐÎÏÇÈ·Á¤«¤é¥¿¥¤¥à¥Ç¥¸¥¿¥¤¥¶k²óÏ©¤òÍѤ¤ÈóƱ´ü¥µ¥ó¥×¥ê¥ó¥°¤ò¹Ô¤¦¡£¥¢¥Ê¥í¥°ºÇ¾®¡¢¥Ç¥¸¥¿¥ë¥ê¥Ã¥Á¤Ê²óÏ©¹½À®¤Ë¤¹¤ë¤³¤È¤Ë¤è¤ê¹â®¡¢¹âÀºÅÙ¤ò¼Â¸½¤¹¤ëÊýË¡¤Ë¤Ä¤¤¤Æ¸¡Æ¤¤·¤¿¡£ |
Âê̾ | A 15-bit 10-Msample/s Pipelined A/D Converter Based on Incomplete Settling Principle |
Ãø¼Ô | ¡ûShuaiqi Wang(Waseda University), Fule Li(Tsinghua University), Yasuaki Inoue(Waseda University) |
Page | pp. 81 - 86 |
Keyword | A/D conversion, pipelined, incomplete settling, low power dissipation |
Abstract | This paper proposes a 15-bit 10-MS/s pipelined ADC based on the incomplete settling principle. The traditional complete settling stage is improved to the incomplete settling structure through dividing the sampling clock of the traditional stage into two parts for discharging the sampling and feedback capacitors and completing the sampling, respectively. It verifies the correction and validity of optimizing ADCs¡¦conversion speed without increasing power consumption through the incomplete settling. This ADC employs scaling-down scheme to achieve low power dissipation and utilizes fullËÅifferential structure, bottom-plate-sampling, and capacitor-sharing techniques as well as bit-by-bit digital self-calibration to increase the ADCÃÔ linearity and accuracy. It is processed in 0.18¡¦ 1P6M CMOS mixed-mode technology. Simulation results show that 82dB SNDR and 87dB SFDR are obtained at the sampling rate of 10MHz with the input sine frequency of 100KHz and the whole static power dissipation is 21.94mW. |
Âê̾ | A Study for the Frequency Analysis of CMOS Analog Multiplier |
Ãø¼Ô | ¡ûQuan Zhang, Zhangcai Huang, Yasuaki Inoue(Waseda University) |
Page | pp. 87 - 91 |
Keyword | CMOS Multiplier, Bandwidth, pole-zero pair |
Abstract | The CMOS implementation of four quadrant multipliers is still a challenging topic for achieving a wide frequency bandwidth. In this paper, a design principle is proposed to construct high frequency CMOS four quadrant multipliers based on the AC properties analysis for typical architectures. The experimental results prove that the proposed principle can be a good refer for frequency design of CMOS analog multipliers. |
Âê̾ | ¥ê¥³¥ó¥Õ¥£¥®¥å¥é¥Ö¥ëRF CMOS̵Àþ½¸ÀѲóÏ©µ»½Ñ |
Ãø¼Ô | ¡û²¬ÅÄ ·ò°ì, Àîź ÂçÊå, ¿û¸¶ ¹°Íº, ±× °ìºÈ(Åìµþ¹©¶ÈÂç³Ø Åý¹ç¸¦µæ±¡) |
Page | pp. 93 - 98 |
Keyword | RF CMOS, ¥ê¥³¥ó¥Õ¥£¥®¥å¥é¥Ö¥ëRF, LNA, multi-standard |
Abstract | Ëܸ¦µæ¤Ç¤Ï¡¤Si CMOSµ»½Ñ¤Ë¤è¤ë¥Þ¥ë¥Á¥¹¥¿¥ó¥À¡¼¥É̵Àþ²óÏ©¤Î¼Â¸½¤Ë¸þ¤±¤Æ¡¤¥ê¥³¥ó¥Õ¥£¥®¥å¥é¥Ö¥ëRF²óÏ©µ»½Ñ¤òÄó°Æ¤¹¤ë¡¥Äó°Æ¤¹¤ë²óÏ©¥¢¡¼¥¥Æ¥¯¥Á¥ã¤Ï¡¤RF²óÏ©Éô¤È¥Ç¥£¥¸¥¿¥ë¤ÎÀ©¸æ²óÏ©¤«¤é¹½À®¤µ¤ì¤Æ¤ª¤ê¡¤¥È¥é¥ó¥¸¥¹¥¿¤ä²ÄÊѼõÆ°ÁǻҤΥХ¤¥¢¥¹ÅÅ°µ¤òÀ©¸æ¤¹¤ë¤³¤È¤Ë¤è¤ê¡¤¤Þ¤¿¡¤²óÏ©¤ò¥Ö¥í¥Ã¥¯¤´¤ÈÀÚ¤êÂؤ¨¤ë¤³¤È¤Ë¤è¤ê¡¤²óÏ©µ¡Ç½¤òưŪ¤ËºÆ¹½À®¤¹¤ë¡¥ºÆ¹½À®µ¡Ç½¤òÍѤ¤¤ë¤³¤È¤Ç¡¤¥Þ¥ë¥Á¥Ð¥ó¥É²½¤Î¤ß¤Ê¤é¤º¡¤Êâα¤Þ¤ê¤Î¸þ¾å¤äÄã¾ÃÈñÅÅÎϲ½¤ò²Äǽ¤È¤¹¤ë¡¥ËܹƤǤϡ¤LNA¤ÎưŪÀǽÊä½þ¤Ë¤è¤ê¡¤ºÇÂç¤Ç80%¤Î¾ÃÈñÅÅÎϺ︺¤òãÀ®¤·¤¿¡¥ |
Âê̾ | Ê£¿ô¥¢¥ó¥Æ¥Ê¤òÍѤ¤¤¿¥Ñ¥Ã¥·¥ÖRFID¥¿¥°¤ÎÄÌ¿®µ÷Î¥ÁýÂç¸ú²Ì¤Ë´Ø¤¹¤ë¸¡Æ¤ |
Ãø¼Ô | ¡ûÈøÊݼê Ìмù, ¼¯»ÒÅè ·û°ì(°ñ¾ëÂç³Ø¹©³ØÉô¥á¥Ç¥£¥¢ÄÌ¿®¹©³Ø²Ê), ¾¾ËÜ Åµ¹ä, ¹ÓÌÚ ·û»Ê(¡Ê³ô¡ËÆüΩÀ½ºî½ê ÆüΩ¸¦µæ½ê) |
Page | pp. 99 - 104 |
Keyword | RFID, ¥¢¥ó¥Æ¥Ê, ÄÌ¿®µ÷Î¥ |
Abstract | ËܹƤǤϡ¤¥Ñ¥Ã¥·¥ÖRFID¥¿¥°¤Î¥¢¥ó¥Æ¥Ê¤òÅŸ»ÍѤÈÊÑÄ´ÍѤËʬ¤±¤ëÊý¼°¤òÄó°Æ¤¹¤ë¡¥ÅŸ»ÍÑ¥¢¥ó¥Æ¥ÊÁǻҤϥѥå·¥ÖRFID¥¿¥°ÅŸ»Ã¼»Ò¤ËÀܳ¤µ¤ì¡¤¤³¤Îü»Ò¤ÎÆþÎÏ¥¤¥ó¥Ô¡¼¥À¥ó¥¹¤Ï¥¢¥ó¥Æ¥Ê¤ÎÆþÎÏ¥¤¥ó¥Ô¡¼¥À¥ó¥¹¤ÎÊ£ÁǶ¦Ìò¤È¤Ê¤Ã¤Æ¤ª¤ê¡¤¸ÇÄê¤Ç¤¢¤ë¡¥°ìÊý¡¤ÊÑÄ´ÍÑ¥¢¥ó¥Æ¥ÊÁǻҤϡ¤¥Ñ¥Ã¥·¥ÖRFID¥¿¥°¤ÎÊÑÄ´ÍÑü»Ò¤ËÀܳ¤µ¤ì¤ª¤ê¡¤¤³¤Îü»Ò¤ÎÆþÎÏ¥¤¥ó¥Ô¡¼¥À¥ó¥¹¤ò¥Ç¥£¥¸¥¿¥ë¾ðÊó¤Î1µÚ¤Ó0¤ËÂбþ¤·¤Æ¡¤¥·¥ç¡¼¥ÈµÚ¤Ó¥ª¡¼¥×¥ó¤ÇÀÚ¤êÂؤ¨¤ë¡¥ |
Âê̾ | (¾·ÂÔ)¿·¤·¤¤£Ó£ï£Ãµ»½Ñ¤òÍѤ¤¤¿»ØÌæǧ¾Ú¥Á¥Ã¥× |
Ãø¼Ô | ¡û½Å¾¾ ÃÒ»Ö, ¿¹Â¼ ¹Àµ¨, ±©ÅÄÌî ¹§Íµ, ÃæÀ¾ ±Ò, Æ£°æ ¹§¼£, ÃÓÅÄ ÆàÈþ»Ò, Åç¼ ½Ó½Å, Ä®ÅÄ ¹îÇ·, ²¬ºê ¹¬É×(£Î£Ô£Ô¥Þ¥¤¥¯¥í¥·¥¹¥Æ¥à¥¤¥ó¥Æ¥°¥ì¡¼¥·¥ç¥ó¸¦µæ½ê) |
Page | pp. 105 - 110 |
Keyword | »ØÌæǧ¾Ú, SoC, »ØÌ楻¥ó¥µ, ¥Ô¥¯¥»¥ë¥¢¥ì¥¤, ²èÁü½èÍý |
Abstract | »ØÌæ¤ÎÆɤ߼è¤ê¤«¤éǧ¾Ú¤Þ¤Ç¤ò¹Ô¤¦»ØÌæǧ¾Ú¥·¥¹¥Æ¥à¤Î¥ï¥ó¥Á¥Ã¥×²½¤Î¤¿¤á¡¢¥Ç¥Ð¥¤¥¹µ»½Ñ¤ä²óÏ©µ»½Ñ¤«¤é¥½¥Õ¥È¥¦¥¨¥¢µ»½Ñ¤Þ¤Ç¤ÎÍÍ¡¹¤ÊÍ×Áǵ»½Ñ¤òÄó°Æ¤·¡¢¤³¤ì¤éµ»½Ñ¤Î¶¨Ä´¤Ë¤è¤ê¥·¥¹¥Æ¥à¤Î¥ï¥ó¥Á¥Ã¥×²½¤ò¼Â¸½¤¹¤ë¿·¤·¤¤SoCµ»½Ñ¤È¡¢¼Â¸½¤·¤¿¥Á¥Ã¥×¤ÎÆÃħ¤ò³è¤«¤¹»ØÌæǧ¾Ú¥¢¥×¥ê¥±¡¼¥·¥ç¥ó¤ò¾Ò²ð¤¹¤ë¡£ |
Âê̾ | (¾·ÂÔ)¥Ð¥¤¥ªÊ¬Ìî¤Ë¤ª¤±¤ë²½³Øȯ¸÷·×¬¤Ø¤Î¥ï¥¤¥ä¥ì¥¹¸÷¥»¥ó¥µ¤Î±þÍÑ |
Ãø¼Ô | ¡ûÌðß· µÁ¾¼, ÅÏî´ °ì´õ, ÂçÀ¾ Ãé»Ö, ³øËÙ À¯ÃË(³ô¼°²ñ¼ÒÆüΩÀ½ºî½êÃæ±û¸¦µæ½ê), ĹëÉô ·òɧ(³ô¼°²ñ¼ÒÆüΩÀ½ºî½ê´ðÁø¦µæ½ê), ðÇÈ ±Éºö(³ô¼°²ñ¼ÒÆüΩĶ£Ì£Ó£É¥·¥¹¥Æ¥à¥º) |
Page | pp. 111 - 116 |
Keyword | ¥Ð¥¤¥ª¥»¥ó¥µ, ¥Ñ¥Ã¥·¥Ö£Ò£ÆÄÌ¿®, DNA, SNP |
Abstract | °Â²Á¤Ç´ÊÊؤʥХ¤¥ª·×¬¥·¥¹¥Æ¥à¤ò¼Â¸½¤¹¤ë¥¡¼¥Ç¥Ð¥¤¥¹¤È¤·¤Æ¥Ñ¥Ã¥·¥ÖRFÄÌ¿®¤È¸÷¥»¥ó¥µµ¡Ç½¤ò2.5mm³Ñ¤Î¥·¥ê¥³¥ó´ðÈľå¤Ë¥â¥Î¥ê¥·¥Ã¥¯½¸ÀѤ·¤¿¥»¥ó¥µ¥Á¥Ã¥×¤ò³«È¯¤·¤¿¡£ËÜ¥Á¥Ã¥×¤òÍѤ¤¤¿·×¬¥·¥¹¥Æ¥à¤Ë¤è¤êDNA¤ò·×¬¤·¡¢°ì±ö´ð¿·¿(SNP: Single Nucleotide Polymorphism)¤ÎƱÄê¤ËÀ®¸ù¤·¤¿¡£ |
Âê̾ | (¾·ÂÔ)¼ê¤Ö¤ì¸¡½ÐÍÑ£²¼´¥¸¥ã¥¤¥í¥â¥¸¥å¡¼¥ë |
Ãø¼Ô | ¡û·ª¸¶ °ìÉ×(¥½¥Ë¡¼³ô¼°²ñ¼Ò) |
Page | pp. 117 - 122 |
Keyword | ¥¸¥ã¥¤¥í, ¿¶Æ°»Ò, ³Ñ®ÅÙ, °µÅÅËì, MEMS |
Abstract | ¥»¥ó¥µÉô¤Ï¡¢MEMS¤ÈÇöËìµ»½Ñ¤Ë¤è¤ê¾®·¿²½¤ò¿Þ¤ë¤È¤È¤â¤Ë¡¢µ¡³£Åª¿¶Æ°¤ò¤·¤ä¤¹¤¤·Á¾õ¤ËºÇŬ²½¤·¤¿¡£¤³¤ÎºÇŬ²½¤È¿·³«È¯IC¤Ç½¾Íè¤Î1¼´¥¸¥ã¥¤¥í¤ÈƱÅù¤Î´¶ÅÙ¤òÊݤÁ¡¢¤µ¤é¤Ë¼þÊÕ²óÏ©¤ò¤âÅëºÜ¤·Ëܥ⥸¥å¡¼¥ë¤ò¼Â¸½¤·¤¿¡£ |
Âê̾ | (¾·ÂÔ)RF¼§µ¤¥»¥ó¥µ¤Ë¤è¤ë¥Á¥Ã¥×¾å¹â¶õ´Öʬ²òǽEMC·×¬ |
Ãø¼Ô | ¡û»³¸ý ÀµÍÎ(ÅìËÌÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê ) |
Page | pp. 123 - 128 |
Âê̾ | ¿Ê²½ÏÀŪ¥Ç¥£¥¸¥¿¥ë¥Õ¥£¥ë¥¿¤ÎÊÂÎó¼Â¸½¤Î¤¿¤á¤Î¹½À®¤È¤½¤Î¥Ï¡¼¥É¥¦¥§¥¢¼Â¸½ |
Ãø¼Ô | °¤Éô Àµ±Ñ, ¡ûÃæß· ÂÀͤ, ÀîËô À¯À¬(ÅìËÌÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²ÊÅŻҹ©³ØÀ칶) |
Page | pp. 129 - 134 |
Keyword | Ŭ±þ¥Ç¥£¥¸¥¿¥ë¥Õ¥£¥ë¥¿, ¿Ê²½ÏÀŪ¥Ç¥£¥¸¥¿¥ë¥Õ¥£¥ë¥¿, ¿Ê²½ÏÀŪ·×»»¼êË¡, ÊÂÎó½èÍý, FPGA |
Abstract | ËܹƤǤϡ¤¿Ê²½ÏÀŪ¥Ç¥£¥¸¥¿¥ë¥Õ¥£¥ë¥¿¡Êevolutionary digital filter: EDF¡Ë¤Î¥¢¥ë¥´¥ê¥º¥à¤¬»ý¤Ä¸ÄÂδ֤Υǡ¼¥¿°Í¸¤¬¾¯¤Ê¤¯¡¤³Æ¸ÄÂΤνèÍý¤¬Æ±°ì¤Ç¤¢¤ë¤È¤¤¤¦ÊÂÎóÀ¤ò¹Íθ¤·¤¿¥Ï¡¼¥É¥¦¥§¥¢¤ò¼Â¸½¤¹¤ë¡¥¤³¤ì¤ò¹Íθ¤·¤¿¥Ï¡¼¥É¥¦¥§¥¢¼Â¸½¤Î¸¡Æ¤¤ò¹Ô¤¤¡¤¤³¤ì¤òFPGA¾å¤Ë¼ÂÁõ¤¹¤ë¡¥¤Þ¤¿¡¤¥Õ¥£¥ë¥¿¥ê¥ó¥°±é»»¤Ë¤ª¤¤¤Æ¡¤Ê£¿ô¤ÎÀÑϱ黻´ï¤òÍѤ¤¤ë¤³¤È¤Ç¡¤±é»»¥ì¥Ù¥ë¤Ç¤ÎÊÂÎó½èÍý¤Î¸ú²Ì¤Ë¤Ä¤¤¤Æ¤Î¸¡Æ¤¤â¹Ô¤¤¡¤¤³¤ì¤òFPGA ¾å¤Ë¼ÂÁõ¤¹¤ë¡¥¤³¤ì¤é¤Î·ë²Ì¡¤Á´¸ÄÂΤ¬ÆþÎÏ¿®¹æ1 ¥µ¥ó¥×¥ë¤ò½èÍý¤¹¤ë¤Î¤ËɬÍפʥ¯¥í¥Ã¥¯¿ô¤Ï¡¤72.6¥¯¥í¥Ã¥¯¤È¤Ê¤ê¡¤¸½ºß¤Þ¤ÇÄó°Æ¤µ¤ì¤Æ¤¤¤ë¼êË¡¤Î1/176.4¤Ëºï¸º¤µ¤ì¤¿. |
Âê̾ | ÀäÂÐÃÍ¸íº¹¤Ë¤è¤ë¥Æ¥ó¥½¥ëÀÑŸ³«¤òÍѤ¤¤¿ÈóÄê¾ï¿®¹æ¤ÎʬΥ |
Ãø¼Ô | ¡ûÈÄ°æ ÍÛ½Ó, °ÂÀî Çî(°¦Ãθ©Î©Âç³Ø), Æâ¾¢ °ï(̾¸Å²°¹©¶ÈÂç³Ø), Ȫ ²í¶³(ÃæÉôÂç³Ø¹©³ØÉô) |
Page | pp. 135 - 140 |
Keyword | ÈóÄê¾ï¿®¹æ, ¿ÊÑÎ̲òÀÏ, ¿®¹æÃê½Ð, ¥Æ¥ó¥½¥ëÀÑŸ³« |
Abstract | ¼çÀ®Ê¬Ê¬ÀϤÏÆþÎÏ¥Ù¥¯¥È¥ë¤ÎÄ㼡¸µ²½¤Ë¤è¤ê¥Ç¡¼¥¿¤¬»ý¤Ä·¹¸þ¤òª¤¨¤ë¤³¤È¤¬¤Ç¤¡¢ÍÍ¡¹¤ÊʬÌî¤Î¥Ç¡¼¥¿¤ËŬÍѤµ¤ì¤Æ¤¤¤ë¤¬¡¢¼çÀ®Ê¬Ê¬ÀϤò»þ·ÏÎó²òÀϤËŬÍѤ¹¤ë¾ì¹ç¤ÏÃåÌܤ·¤Æ¤¤¤ëÀ®Ê¬¤¬Äê¾ï¤Ç¤¢¤ë¤³¤È¤¬¾ò·ï¤È¤Ê¤ë¡£ËܹƤǤÏ2¼¡ÊÑ¿ô´Ø¿ô¤Ë¤ª¤¤¤Æ¼çÀ®Ê¬Ê¬ÀϤÈÅù²Á¤Ç¤¢¤ë¥Æ¥ó¥½¥ëÀÑŸ³«¤ò³ÈÄ¥¤·¡¢Â¿ÊÑÎÌ¿®¹æ¤«¤éÈóÄê¾ï¿®¹æ¤òÃê½Ð¤¹¤ë¼êË¡¤òÄó°Æ¤¹¤ë¡£2ÊÑ¿ô´Ø¿ô¤òÁÛÄꤷ¤¿¾ì¹ç¡¢½¾Íè¤Î¥Æ¥ó¥½¥ëÀÑŸ³«¤ÏÆþÎÏ¥Ù¥¯¥È¥ë¤È¤Îº¹Ê¬¤Î¼«¾è¸íº¹¤¬ºÇ¾®¤È¤Ê¤ë2¤Ä¤Î1ÊÑ¿ô´Ø¿ô¤ÎÀѤòµá¤á¤ë¤¬¡¢ËܹƤǤÏ1ÊÑ¿ô´Ø¿ô¤ÎÀѤËľήÀ®Ê¬¤ò¿äÄꤹ¤ë¹à¤ò²Ã¤¨¡¢¼«¾è¸íº¹¤òÀäÂÐÃÍ¸íº¹¤Ë¤¹¤ë¤³¤È¤Ë¤è¤êÈóÄê¾ï¿®¹æ¤ÎʬΥ¤¬²Äǽ¤Ç¤¢¤ë¤³¤È¤ò¼¨¤¹¡£ |
Âê̾ | A Refined Filtering Approach to Adaptive Line Enhancement |
Ãø¼Ô | ¡ûYusuke Tsuda(ºë¶ÌÂç³ØÂç³Ø±¡Íý¹©³Ø¸¦µæ²Ê), Tetsuya Shimamura(ºë¶ÌÂç³Ø¹©³ØÉô¾ðÊó¥·¥¹¥Æ¥à¹©³Ø²Ê) |
Page | pp. 141 - 146 |
Keyword | adaptive line enhancer, NLMS algorithm |
Abstract | We propose a novel filtering technique for an adaptive line enhancer (ALE). The ALE is based on a linear transversal filter and updated by the normalized least mean square (NLMS) algorithm. The proposed filtering technique is to obtain a refined output signal by linear convolution of the updated coefficient vector and the current input vector. Theoretical analysis and computer simulation demonstrate the effectiveness of the RF technique. |
Âê̾ | Performance Evaluation of Motion-Compensated Spatio-Temporal Filtering with Spatial DWT |
Ãø¼Ô | ¡ûMinoru Hiki, Takuma Ishida, Shogo Muramatsu, Hisakazu Kikuchi(Dept. of Electrical and Electronic Engineering, Niigata University) |
Page | pp. 147 - 152 |
Keyword | Motion-compensated temporal filtering, 3-D filter banks, scalability, video coding, suppress PSNR fluctuation |
Abstract | In this work, a novel hierarchical motion-compensated spatio-temporal filtering (MCSTF) is proposed for scalable video coding. MCSTF is an alternative technique of existing motion-compensated temporal filtering (MCTF), a fundamental component for scalable video coding in next generation. MCSTF is a non-separable sub-sampling version of MCTF and provides interlaced pictures as intermediate video sequence by using a spatio-temporal split process. Furthermore, the 1/3-transform structure, which excludes the lifting update-step, significantly suppresses the PSNR fluctuation which occurs in the existing MCTF technique. Our proposed system has an advantage of suppressing PSNR fluctuation with almost the same average PSNR as that of existing MCTF. Some experimental results with entropy coded scalar quantization show the significance of our proposed technique. |
Âê̾ | A Strict Successive Elimination Algorithm for Fast Motion Estimation |
Ãø¼Ô | ¡ûYang Song(Graduate School of IPS, Waseda University), Zhenyu Liu(RISE, Waseda University), Takeshi Ikenaga, Satoshi Goto(Graduate School of IPS, Waseda University) |
Page | pp. 153 - 157 |
Keyword | Motion Estimation, SEA, MSEA, Strict SEA |
Abstract | This paper present a simple and effective method to further reduce the search positions in successive elimination algorithm (SEA). Because the SEA values for most of the best matching search positions are much smaller than the current minimum SAD, we can simply increase the calculated SEA value to increase the elimination ratio without much affecting the coding efficiency. Experiments show that the proposed strict SEA algorithm (SSEA) can eliminate more than 70% of the search positions in SEA algorithm, and the maximum average PSNR and bitrate losses are 0.13dB and 3.33%, respectively. The proposed method also can be used in multilevel SEA (MSEA) and fine granularity SEA (FGSE) algorithms, and the corresponding factors for MSEA and associated experiments data are also given in this paper. |
Âê̾ | Loss Free VLSI Oriented Full Computation Reusing Algorithm for H.264 Fractional Motion Estimation |
Ãø¼Ô | ¡ûMing Shao(The Graduate School of Information, Production and systems, Waseda University), Zhenyu Liu(Kitakyushu Foundation for the Advancement of Industry, Science and Technology), Satoshi Goto, Takeshi Ikenaga(The Graduate School of Information, Production and systems, Waseda University) |
Page | pp. 159 - 164 |
Keyword | H.264, FME, reusing, VLSI, loss free |
Abstract | Fractional motion estimation (FME) is an advanced feature adopted in H.264/AVC video compression standard with quarter-pixel accuracy. Although FME could gain up to 5db encoding efficiency, sub-pixel interpolation and SATD computation, as main parts of FME, require a large mount of computation complexity. To reduce the complexity of FME, this paper proposes a full computation reusable VLSI oriented algorithm. Through exploiting the similarity among motion vectors (MVs), temporary computation results can be fully reused by other sub-blocks. Furthermore, since a simple, neat and effective searching method is adopted, the proposed method is very suitable for VLSI implementation. Experiment results shows that up to 50% add operations and 80% external memory access operations are saved without any deterioration in the coding quality. |
Âê̾ | ²ÄÊÑ¥¦¥£¥ó¥É¥¦¥¹¥Æ¥ì¥ª¥Þ¥Ã¥Á¥ó¥°¥×¥í¥»¥Ã¥µ¤Î¥¢¡¼¥¥Æ¥¯¥Á¥ã |
Ãø¼Ô | µÜËÜ Î¶²ð, ¡ûÎ ºÜ·®, Åû°æ ¹°, Ãæ¼ ¹Ô¹¨(µþÅÔÂç³ØÂç³Ø±¡¾ðÊó³Ø¸¦µæ²ÊÄÌ¿®¾ðÊó¥·¥¹¥Æ¥àÀ칶) |
Page | pp. 165 - 170 |
Keyword | stereo, processor architecture |
Abstract | ¥¹¥Æ¥ì¥ª»ë¤Ë¤ª¤± ¤ëÂбþÅÀõº÷¤Ç¤¢¤ë¥¹¥Æ¥ì¥ª¥Þ¥Ã¥Á¥ó¥°¤Ï¿¤¯¤Î·×»»Î̤òÍפ·¡¤Æà ¤Ë¡¤¹âÀºÅ٤ʥޥåÁ¥ó¥°¼êË¡¤Ï¤è¤ê¿¤¯¤Î·×»»Î̤¬É¬ÍפȤʤ롥¤½ ¤Î¤¿¤á¡¤Áȹþ¤ßʬÌî¤Ë¤ª¤±¤ëÍøÍѤΤ¿¤á¤Ë¡¤¼Â»þ´Ö½èÍý¥·¥¹¥Æ¥à¤ä ÀìÍÑ¥×¥í¥»¥Ã¥µ¤Î³«È¯¤¬¹Ô¤ï¤ì¤Æ¤¤¤ë¤¬¡¤¹âÀºÅ٥ޥåÁ¥ó¥°¤È¼Â»þ ´Ö½èÍý¤òξΩ¤¹¤ë¥·¥¹¥Æ¥à¤Ï¸ºß¤·¤Ê¤¤¡¥ËܹƤǤϡ¤¶áǯ¤Î¥¹¥Æ¥ì ¥ª¥Þ¥Ã¥Á¥ó¥°¥¢¥ë¥´¥ê¥º¥à¤Ë¤ª¤±¤ë¸¦µæ¤ÎÀ®²Ì¤Ë´ð¤Å¤¡¤¹âÀºÅÙ¤« ¤Ä¹â®¤Ê¼êË¡¤Ç¤¢¤ë²ÄÊÑ¥¦¥£¥ó¥É¥¦¥¹¥Æ¥ì¥ª¥Þ¥Ã¥Á¥ó¥°¼êË¡¤Î¥ê¥¢ ¥ë¥¿¥¤¥à¼Â¹Ô¤òÌܻؤ·¤¿¥×¥í¥»¥Ã¥µ¥¢¡¼¥¥Æ¥¯¥Á¥ã¤ÎÄó°Æ¤ò¹Ô¤¤¡¤ ½èÍýÀǽ¤ÈÊÂÎóÅ٤δط¸¤ò¼¨¤·¤¿¡¥ |
Âê̾ | Image Enhancement by Committee Machine with Symbiotic Evolution |
Ãø¼Ô | ¡ûNoriko Otani(Musashi Institute of Technology), Tomoaki Kimura(IBM Japan), Katsumi Nitta(Tokyo Institute of Technology) |
Page | pp. 171 - 176 |
Keyword | Symbiotic Evolution, Committee Machine, Image Enhancement |
Abstract | In this paper, we present a novel approach to learning parameters of a committee machine which is used to enhance the blurred Gaussian noisy images. It is based on symbiotic evolution, which is a kind of Genetic Algorithm, to avoid overlearning and find an optimal solution in various candidates. We experimented in enhancement of various noisy images with various variance. The experimental results show that the proposed method doesn't depend on noise variance or the type of image, and the committee decision machine learned by the proposed method realized the noisy image enhancement superior than former methods. |
Âê̾ | Improvement of Iterative Methods for Image Deconvolution Based on Subregion Decomposition and Optimal Local Iterations |
Ãø¼Ô | ¡ûKarn Patanukhom, Akinori Nishihara(Tokyo Institute of Technology) |
Page | pp. 177 - 182 |
Keyword | Image Deconvolution, Image Restoration, Iterative methods, Subregion |
Abstract | A technique based on subregion decomposition and optimal local iteration is proposed for iterative image deconvolution methods. The proposed technique improves restoration results of the conventional deconvolution methods by separately restoring each subregion of an image with different numbers of optimal local iteration. In order to decompose the image into subregion, an algorithm based on analysis of blur component is introduced. In addition, to estimate of the optimal local iteration, an error-analysis- based approach is also introduced. Simulation results are presented to demonstrate the promising performance of the proposed techniques. |
Âê̾ | ¿¿ô·èµ¡³£¤òÍѤ¤¤¿¥¤¥ó¥Ñ¥ë¥¹À»¨²»¤Î¸¡½ÐË¡ |
Ãø¼Ô | ¡ûÂçë µª»Ò(É𢹩¶ÈÂç³Ø´Ä¶¾ðÊó³ØÉô), ÌÚ¼ À¿Áï(ÆüËÜIBM³ô¼°²ñ¼Ò), ¿·ÅÄ ¹î¸Ê(Åìµþ¹©¶ÈÂç³Ø) |
Page | pp. 183 - 188 |
Keyword | ¿¿ô·èµ¡³£, »¨²»¸¡½Ð |
Abstract | ËܹƤǤϡ¤¥¤¥ó¥Ñ¥ë¥¹À»¨²»¤Î¿·¤·¤¤¸¡½ÐÊýË¡¤È¤·¤Æ¡¤½èÍýÅÀ¤È¶á˵Îΰè¤È¤Îº¹Ê¬¤ò¿¿ô·èµ¡³£¤ËÆþÎϤ¹¤ë¤³¤È¤Ç¡¤½èÍýÅÀ¤Ë¥¤¥ó¥Ñ¥ë¥¹À»¨²»¤¬½Å¾ö¤·¤Æ¤¤¤ë¤«Èݤ«¤òȽÃǤ¹¤ë¸¡½ÐÊýË¡¤òÄó°Æ¤¹¤ë¡¥½¾ÍèÊýË¡¤Ç¤Ï¡¤¥é¥ó¥À¥àÃÍ¥¤¥ó¥Ñ¥ë¥¹À»¨²»¤ËÂФ·¤Æ¸ú²Ì¤¬¤Ê¤«¤Ã¤¿¤ê¡¤¥é¥ó¥À¥àÃÍ¥¤¥ó¥Ñ¥ë¥¹À»¨²»¤ËÂФ·¤Æ»¨²»È¯À¸³ÎΨ¤Ë°Í¸¤·¤¿¥Ñ¥é¥á¡¼¥¿¤òÀßÄꤹ¤ëɬÍפ¬¤¢¤ë¤¬¡¤Äó°ÆË¡¤Ç¤ÏÍ£°ì¤Î¥Ñ¥é¥á¡¼¥¿¤ÇÍÍ¡¹¤Ê¼ïÎà¤Î²èÁü¤ò½èÍý¤¹¤ë¤³¤È¤¬¤Ç¤¤ë¡¥¥Ù¥ó¥Á¥Þ¡¼¥¯¥Ç¡¼¥¿¤ËŬÍѤ·¤¿·ë²Ì¡¤²èÁü¤Î¼ïÎà¤ä»¨²»È¯À¸³ÎΨ¤Ë°Í¸¤¹¤ë¤³¤È¤Ê¤¯¡¤¸ÇÄêÃͤª¤è¤Ó¥é¥ó¥À¥àÃÍ¥¤¥ó¥Ñ¥ë¥¹À»¨²»¤ËÂФ·¤Æ¡¤½¾ÍèÊýË¡¤ÈƱÅù¤Þ¤¿¤Ï¤½¤ì°Ê¾å¤ÎÀǽ¤Ç¤¢¤ë¤³¤È¤ò³Îǧ¤·¤¿¡¥ |
Âê̾ | ¿½Å²èÁü¤ÎÅý¹ç¤Ë¤è¤ëÆ°¤¥Ö¥ì¤òȼ¤ï¤Ê¤¤¥«¥é¡¼¥À¥¤¥Ê¥ß¥Ã¥¯¥ì¥ó¥¸¤Î³ÈÄ¥ |
Ãø¼Ô | µÜËÜ Î¶²ð(µþÅÔÂç³ØÂç³Ø±¡¾ðÊó³Ø¸¦µæ²ÊÄÌ¿®¾ðÊó¥·¥¹¥Æ¥àÀ칶), ¡û¸¶ ͪµ(µþÅÔÂç³Ø¹©³ØÉôÅŵ¤ÅŻҹ©³Ø²Ê), Åû°æ ¹°, Ãæ¼ ¹Ô¹¨(µþÅÔÂç³ØÂç³Ø±¡¾ðÊó³Ø¸¦µæ²ÊÄÌ¿®¾ðÊó¥·¥¹¥Æ¥àÀ칶) |
Page | pp. 189 - 192 |
Keyword | multiple exposure, fusion, motion blur |
Abstract | ¼ÖºÜ¤ä´Æ»ëÍÑÅӤˤª¤¤¤Æ¤Ï¡¤¥«¥á¥é¤Ë¤è¤ë»£Áü»þ¤Ë¹¤¤¥À¥¤¥Ê¥ß¥Ã ¥¯¥ì¥ó¥¸¤¬Í׵ᤵ¤ì¤ë¡¥»£Áü²áÄø¤Ë¤ª¤±¤ë¥À¥¤¥Ê¥ß¥Ã¥¯¥ì¥ó¥¸¤Î³È Ä¥¼êË¡¤Î1¤Ä¤Ë¿½ÅϪ¸÷²èÁü¤ÎÅý¹ç¤¬¤¢¤ë¡¥Â¿½ÅϪ¸÷²èÁü¤ÎÅý¹ç¤Ë ¤è¤Ã¤Æ¥«¥é¡¼¥À¥¤¥Ê¥ß¥Ã¥¯¥ì¥ó¥¸¤ò³ÈÄ¥¤¹¤ë¼êË¡¤ÏÄó°Æ¤µ¤ì¤Æ¤¤¤ë ¤¬¡¤Èï¼ÌÂΤÎÆ°¤¤ò¹Íθ¤·Æ°¤¥Ö¥ì¤ò½üµî¤¹¤ë¼êË¡¤ÏÄó°Æ¤µ¤ì¤Æ¤¤ ¤Ê¤¤¡¥¤½¤³¤Ç¡¤ËܹƤǤϡ¤Ïª¸÷»þ´ÖÀ©¸æ¤Ë¤è¤Ã¤ÆÆÀ¤é¤ì¤¿Â¿½Å²èÁü ¤òÂоÝʪ¤ÎÆ°¤¤ò¿äÄꤷ¤Ä¤ÄÅý¹ç¤¹¤ë¤³¤È¤Ë¤è¤Ã¤Æ¡¤Æ°¤¥Ö¥ì¤Î¤Ê ¤¤¹¥À¥¤¥Ê¥ß¥Ã¥¯¥ì¥ó¥¸¥«¥é¡¼²èÁü¤ò¹çÀ®¤¹¤ë¼êË¡¤òÄó°Æ¤¹¤ë¡¥ |
Âê̾ | (¾·ÂÔ)MPEG ¥ª¡¼¥Ç¥£¥ª¤ÎºÇ¿·Æ°¸þ¤È±þÍÑ |
Ãø¼Ô | ¡ûÌî¼ ½ÓÇ·(NEC ¥á¥Ç¥£¥¢¾ðÊ󸦵æ½ê) |
Page | pp. 193 - 198 |
Keyword | MPEG, ¥ª¡¼¥Ç¥£¥ªÉä¹æ²½ |
Abstract | ISO/IEC ¤Ë¤ª¤±¤ë¥ª¡¼¥Ç¥£¥ªÉä¹æ²½¤Îɸ½à²½Æ°¸þ¤òƧ¤Þ¤¨¡¤µ»½ÑŪ¤ÊŸ˾¤È²ÝÂꡤ¸¦µæ»öÎã¤ò¾Ò²ð¤¹¤ë¡¥ |
Âê̾ | (¾·ÂÔ)ÃÎŪ¾ðÊó¥¢¥¯¥»¥¹¤ò¼Â¸½¤¹¤ë¤¿¤á¤Î±ÇÁü¸¡º÷¤Ë´Ø¤¹¤ë¸¦µæÆ°¸þ |
Ãø¼Ô | ¡ûĹ뻳 Èþµª(Ë̳¤Æ»Âç³ØÂç³Ø±¡ ¾ðÊó²Ê³Ø¸¦µæ²Ê) |
Page | pp. 199 - 203 |
Keyword | ²èÁü¸¡º÷, ±ÇÁü¥¤¥ó¥Ç¥¥·¥ó¥°, ¾ðÊó¥¢¥¯¥»¥¹ |
Abstract | ¾ðÊóÂç¹Ò³¤»þÂå¤ò·Þ¤¨ÍøÍѼԤÎÃÎŪÍßµá¤òËþ¤¿¤¹¾ðÊó¥¢¥¯¥»¥¹µ»½Ñ¤Î³«È¯¤¬µÞ̳¤È¤µ¤ì¤Æ¤¤¤ë¡¥Ëֱܹé¤Ç¤Ï¡¤¤½¤Î¼çÍ×µ»½Ñ¤È¤µ¤ì¤ë¡¤±ÇÁü¥Ç¡¼¥¿¤Î¸¡º÷¤ÈʬÎà¤Ë¤Ä¤¤¤Æ¸½¾õ¤Î¸¦µæÆ°¸þ¤ò¾Ò²ð¤¹¤ë¡¥ |
Âê̾ | ²»À¼Ç§¼±¥·¥¹¥Æ¥à¤Î¥Ï¡¼¥É¥¦¥§¥¢²½ |
Ãø¼Ô | ¡ûºÍÄÔ À¿(¶áµ¦Âç³ØÍý¹©³ØÉôÅŵ¤ÅŻҹ©³Ø²Ê), ¾¾Ìî ͵Ƿ(¶áµ¦Âç³ØÂç³Ø±¡Áí¹çÍý¹©³Ø¸¦µæ²Ê¥¨¥ì¥¯¥È¥í¥Ë¥¯¥¹·Ï¹©³ØÀ칶), ±üÅÄ ¿¿Ç¡(¶áµ¦Âç³ØÍý¹©³ØÉôÅŵ¤ÅŻҹ©³Ø²Ê), »³ÅÄ ¹¸µ×(¥·¥ã¡¼¥×(³ô) ÅŻҥǥХ¤¥¹³«È¯ËÜÉô Àèüµ»½Ñ³«È¯¸¦µæ½ê), ¿À¸Í ¾°»Ö(¶áµ¦Âç³Ø Íý¹©³ØÉô Åŵ¤ÅŻҹ©³Ø²Ê) |
Page | pp. 205 - 210 |
Keyword | ²»À¼Ç§¼±¤Î¥Ï¡¼¥É¥¦¥§¥¢²½ |
Âê̾ | FIFO¥Ð¥Ã¥Õ¥¡¤Ë¤è¤ë¹â¸úΨMessage-Passing¥¹¥±¥¸¥å¡¼¥ë¤òÍѤ¤¤¿LDPCÉü¹æ´ï |
Ãø¼Ô | ¡ûÀ¶¿å °ìÈÏ, ÀÐÀî ãǷ(Áá°ðÅÄÂç³ØÂç³Ø±¡¾ðÊóÀ¸»º¥·¥¹¥Æ¥à¸¦µæ²Ê), ¸ÍÀî ˾(Áá°ðÅÄÂç³ØÍý¹©³ØÉô¥³¥ó¥Ô¥å¡¼¥¿¡¦¥Í¥Ã¥È¥ï¡¼¥¯¹©³Ø²Ê), ÃÓ±Ê ¹ä, ¸åÆ£ ÉÒ(Áá°ðÅÄÂç³ØÂç³Ø±¡¾ðÊóÀ¸»º¥·¥¹¥Æ¥à¸¦µæ²Ê) |
Page | pp. 211 - 216 |
Keyword | LDPCÉä¹æ, Message-Passing Schedule, FPGA, FIFO¥Ð¥Ã¥Õ¥¡ |
Abstract | ËܹƤǤϡ¤¹â¸úΨMessage-Passing¥¹¥±¥¸¥å¡¼¥ë¤òŬÍѤ¹¤ë¤³¤È¤¬²Äǽ¤ÊLDPCÉü¹æ´ï¤Ë¤ª¤±¤ë¥á¥â¥ê¤ÎÀêÍÌÌÀѤòºï¸º¤¹¤ë¤¿¤á¤Ë¡¤(1) ¹â¸úΨMessage-Passing¥¹¥±¥¸¥å¡¼¥ë¤òSingle Port¥á¥â¥ê¤Ç¼Â¸½¤¹¤ë¼êË¡¡¤(2) Á´¤Æ¤Î¥á¥â¥ê¥Ð¥ó¥¯¤òFIFO¥Ð¥Ã¥Õ¥¡¤òÍѤ¤¤Æ¼Â¸½¤¹¤ë¼êË¡¤òÄó°Æ¤·¤¿¡¥Äó°Æ¼êË¡¤òŬÍѤ·¤Æ¡¤FPGA (Virtex xc2v6000)¤Ë¼ÂÁõ¤·¤¿·ë²Ì¡¤½¾Íè¼êË¡¤ÈÈæ³Ó¤·¤Æ¡¤Ìó30%¤Î¥á¥â¥êÍÆÎ̤¬ºï¸º¤Ç¤¡¤LDPCÉü¹æ´ïÁ´ÂΤˤª¤±¤ëÌó15%¤ÎFPGA SLICE¿ô¤òºï¸º¤Ç¤¤ë¤³¤È¤ò³Îǧ¤·¤¿¡¥ |
Âê̾ | ¿¹à¼°¶á»÷¤Ë¤è¤ëÇÜÀºÅÙ½éÅù´Ø¿ô±é»»²óÏ©¤ÎÌÌÀÑ-ÃÙ±äºÇŬ²½¼êË¡ |
Ãø¼Ô | ¡û¶¶ËÜ ¹ÀÆó, ¥â¥·¥Ë¥ã¥¬¥ï¥·¥ê¡¼(Ê¡²¬Âç³Ø¹©³ØÉôÅŻҾðÊ󹩳زÊ), ¼¾å Ͼ´(¶å½£Âç³Ø¥·¥¹¥Æ¥à¾ðÊó²Ê³Ø¸¦µæ±¡¾ðÊóÍý³ØÉôÌç) |
Page | pp. 217 - 222 |
Keyword | ½éÅù´Ø¿ô, ÇÜÀºÅÙ·×»», ºÇŬ²½ |
Abstract | Hardware implementation of IEEE-754 double-precision elementary functions, such as square root, reciprocal, etc, requires search for a tradeoff between the logic gate/wire area and the look-up table area. In this paper, we propose a new technique to reduce both the look-up table size and access latency of IEEE-754 double-precision elementary functions. Simulations show that the optimization reduces the total memory requirements for five elementary functions by 1/50 while almost the same computation delay. The technique is simple yet suitable for the SoC design of arithmetic modules. |
Âê̾ | ÄÌ¿®ÉʼÁ¤ò¹Íθ¤·¤¿¥Ç¥£¥¸¥¿¥ë̵ÀþÄÌ¿®¥·¥¹¥Æ¥à¤Î¾ÃÈñ¥¨¥Í¥ë¥®¡¼²òÀÏ |
Ãø¼Ô |  ¹¬Í´(¶å½£Âç³ØÂç³Ø±¡¥·¥¹¥Æ¥à¾ðÊó²Ê³ØÉÜ), ¡û¼¼»³ ¿¿ÆÁ(¶å½£Âç³Ø¥·¥¹¥Æ¥àLSI¸¦µæ¥»¥ó¥¿¡¼), °Â±º ´²¿Í(¶å½£Âç³ØÂç³Ø±¡¥·¥¹¥Æ¥à¾ðÊó²Ê³Ø¸¦µæ±¡) |
Page | pp. 223 - 228 |
Keyword | Äã¾ÃÈñ¥¨¥Í¥ë¥®¡¼, ¥Ç¥£¥¸¥¿¥ë̵ÀþÄÌ¿®, ÄÌ¿®ÉʼÁ |
Abstract | ¥Ç¥£¥¸¥¿¥ë̵ÀþÄÌ¿®µ»½Ñ¤òÍøÍѤ·¤¿¥¢¥×¥ê¥±¡¼¥·¥ç¥ó¤ËÂФ¹¤ë¾ÃÈñ¥¨¥Í¥ë¥®¡¼¤Îºï¸ºÍ׵᤬Èó¾ï¤Ë¶¯¤¤¡£ËܹƤϡ¢ÄÌ¿®ÉʼÁ¤È¾ÃÈñ¥¨¥Í¥ë¥®¡¼¤Î´Ø·¸¤ËÃåÌܤ·¡¢¤¢¤ë°ìÄê°Ê¾å¤ÎÄÌ¿®ÉʼÁ¤ò³ÎÊݤ·¤Ä¤Ä¾ÃÈñ¥¨¥Í¥ë¥®¡¼¤òºï¸º¤¹¤ë¤³¤È¤òÌÜŪ¤È¤¹¤ë¡£ÄÌ¿®¤ò¹Ô¤¦¥¢¥×¥ê¥±¡¼¥·¥ç¥ó¤´¤È¤ËÍ¿¤¨¤é¤ì¤ëÄÌ¿®ÉʼÁ¤ò³ÎÊݤ·¤Ä¤Ä¡¢¥Ñ¥±¥Ã¥ÈĹ¡¦ÊÑÄ´Êý¼°¤È¤¤¤Ã¤¿Ê£¿ô¤Î¥Ñ¥é¥á¡¼¥¿¤òƱ»þ¤ËºÇŬ²½¤·¡¢¤Þ¤¿¡¢Á÷¿®¿®¹æÅÅÎÏ¡¦¿®¹æ½èÍý±é»»ÀºÅ٤Ȥ¤¤Ã¤¿²óÏ©¥Ñ¥é¥á¡¼¥¿À©¸æ¤òŬÀڤ˹Ԥ¦¤³¤È¤Ë¤è¤êÄã¾ÃÈñ¥¨¥Í¥ë¥®¡¼²½¤òÌܻؤ¹¡£¤½¤Î½àÈ÷¤È¤·¤Æ¡¢ÄÌ¿®ÉʼÁ¤ò¹Íθ¤·¤¿¥Ç¥£¥¸¥¿¥ë̵ÀþÄÌ¿®¥·¥¹¥Æ¥à¤Î¾ÃÈñ¥¨¥Í¥ë¥®¡¼¤ò²òÀϤ¹¤ë¡£ |
Âê̾ | À߷׺ÆÍøÍѤΰ٤Υץí¥È¥³¥ëÊÑ´¹´ï¹çÀ®¼êË¡ |
Ãø¼Ô | ¡ûÅÏî´ æÆÂÀ(ÅìµþÂç³ØÂç³Ø±¡ ¹©³Ø·Ï¸¦µæ²Ê), À¥¸Í ¸¬½¤(ÅìµþÂç³ØÂ絬ÌϽ¸ÀÑ¥·¥¹¥Æ¥àÀ߷׶µ°é¸¦µæ¥»¥ó¥¿¡¼), ÀÐÀî ͪ»Ê(ÅìµþÂç³Ø ¹©³ØÉô), ¾®¾¾ Áï, Æ£ÅÄ ¾»¹¨(ÅìµþÂç³ØÂ絬ÌϽ¸ÀÑ¥·¥¹¥Æ¥àÀ߷׶µ°é¸¦µæ¥»¥ó¥¿¡¼) |
Page | pp. 229 - 234 |
Keyword | SoC, ¥×¥í¥È¥³¥ëÊÑ´¹, ¥¤¥ó¥¿¡¼¥Õ¥§¥¤¥¹¹çÀ®, IPºÆÍøÍÑ |
Abstract | ¼ÂºÝ¤ËSoC¤ÎÀ߷פÇÍøÍѤµ¤ì¤Æ¤¤¤ëÊ£»¨¤Ê¥×¥í¥È¥³¥ë¤ËÂФ·¤ÆŬÍѲÄǽ¤Ê¥×¥í¥È¥³¥ëÊÑ´¹´ï¤Î¼«Æ°¹çÀ®µ»½Ñ¤òÄó°Æ¤¹¤ë¡£Äó°Æ¼êË¡¤Ï£³¤Ä¤ÎÍ×Áǵ»½Ñ¡§¥×¥í¥È¥³¥ë¥â¥Ç¥ê¥ó¥°¼êË¡¡¢¥ë¡¼¥×¥¨¥Ã¥¸¤Î½èÍý¡¢¥¹¡¼¥Ñ¡¼¥¹¥Æ¡¼¥È¤ÎƳÆþ¤Ë¤è¤Ã¤Æ¹½À®¤µ¤ì¡¢Ìµ¸Â¤Ë³¤¯¥×¥í¥È¥³¥ë¤Î¥È¥é¥ó¥¶¥¯¥·¥ç¥ó¤ò°·¤¦¤³¤È¤¬¤Ç¤¤ë¡£¤Þ¤¿¡¢³Æ¥·¡¼¥±¥ó¥¹¤òÆÈΩ¤Ë°·¤¤¡¢·×»»Î̤òºï¸º¤¹¤ë¤³¤È¤¬¤Ç¤¤ë¡£¤³¤ì¤é¤òÍѤ¤¤ë¤³¤È¤Ë¤è¤ê¡¢´û¸µ»½Ñ¤ÎŬÍѲÄǽÈϰϤò³ÈÂ礹¤ë¤³¤È¤¬¤Ç¤¤ë¡£ËÜÏÀʸ¤Ç¤Ï¡¢AMBA¡¦OCP´Ö¤Î¥×¥í¥È¥³¥ëÊÑ´¹´ï¤ò¹çÀ®¤·¡¢Äó°Æ¼êË¡¤Î͸úÀ¤ò¼¨¤¹¡£ |
Âê̾ | Ãٱ䡦ÌÌÀѤΥȥ졼¥É¥ª¥Õ¤ò¹Íθ¤·¤¿²Ã»»´ïÍÑ prefix graph¤Î¹½À®¼êË¡¤Ë¤Ä¤¤¤Æ |
Ãø¼Ô | ¡û¾¾±Ê ¿ÉÄ»Ò(Ê¡²¬ÃÎŪ¥¯¥é¥¹¥¿¡¼¸¦µæ½ê), ¾¾±Ê ͵²ð(¶å½£Âç³Ø) |
Page | pp. 235 - 240 |
Keyword | ±é»»´ï¹çÀ®, parallel prefix adder |
Abstract | ²Ã»»´ï¤Î¹çÀ®¤Ë¤ª¤¤¤Æ¤Ï¡¢¤Þ¤º¸ÄÊ̤Υƥ¯¥Î¥í¥¸¾ðÊó¤È¤ÏÆÈΩ¤Ë³µÎ¬¹½Â¤¤ò°ì °Õ¤Ë·è¤á,¤½¤ì¤ËÂФ·¤ÆÂоݤȤ·¤Æ¤¤¤ë¥é¥¤¥Ö¥é¥ê¤Î¥»¥ë¤Ë¥Æ¥¯¥Î¥í¥¸¥Þ¥Ã¥Ô ¥ó¥°¤ò¹Ô¤¦¤È¤¤¤¦2Ãʳ¬¤Î²áÄø¤Ç¼Â¸½¤µ¤ì¤ë¤³¤È¤¬Â¿¤¤¡£¤·¤«¤·¡¢¤è¤êÉʼÁ¤ò¤¢¤²¤ë¤¿¤á¤Ë¤Ï¡¢³µÎ¬¹½Â¤¤Î·èÄê¤È¥Þ¥Ã¥Ô¥ó¥°¤È¤òÍ»¹ç¤·¡¢¾ÜºÙ¤Ê¾ðÊó¤ò¹Íθ¤·¤Ä¤Ä³µÎ¬¹½Â¤¤ò·èÄꤹ¤ë¤³¤È¤¬Ë¾¤Þ¤·¤¤¡£ËܹƤǤϡ¢¤è¤ê¹âÉʼÁ¤Ê²Ã»»´ï¹çÀ®¤Î¤¿¤á¤Î°ì¤Ä¤ÎÏÈÁȤߤȤ·¤Æ¡¢ÃÙ±ä/ÌÌÀѤËÉý¤ò»ý¤¿¤»¤¿Ê£¿ô¤Î³µÎ¬¹½Â¤¤ò¸õÊä¤È¤·¤ÆÀ¸À®¤·¡¢¤½¤ì¤é¤ËÂФ·¤Æ¥Þ¥Ã¥Ô¥ó¥°¤ò¹Ô¤¦¤³¤È¤òÁ°Äó¤È¤·¤Æ¡¢ÌÌÀÑ¡¿ÃÙ±ä¤Î¥È¥ì¡¼¥É¥ª¥Õ¤ò¹Íθ²Äǽ¤Ê³µÎ¬¹½Â¤½¸¹ç¤òÀ¸À®¤¹¤ë¼êË¡¤òÄó°Æ¤¹¤ë¡£Parallel prefix adder ¤òÂоݤȤ·¤Æ¼êË¡¤ò¼Â¸½¤·¡¢¼Â¸³¤òÄ̤·¤Æɾ²Á¡¿¹Í»¡¤ò¹Ô¤¦¡£¡¡ |
Âê̾ | ¥¢¥Ê¥í¥°ICÀ߷פˤª¤±¤ëÌÚɽ¸½¤òÍѤ¤¤¿ÇÛÃÖ¼êË¡ |
Ãø¼Ô | ¡ûÊ¿Àî ºÚÄÅÈþ(ÅìµþÇÀ¹©Âç³ØÂç³Ø±¡ Åŵ¤ÅŻҹ©³ØÀ칶), Æ£µÈ Ë®ÍÎ(ÅìµþÇÀ¹©Âç³Ø) |
Page | pp. 241 - 246 |
Keyword | O-tree, ÂоÎÇÛÃÖÀ©Ìó, ¥¢¥Ê¥í¥°IC¥ì¥¤¥¢¥¦¥È |
Abstract | ¹âÀǽ¥¢¥Ê¥í¥°IC¥ì¥¤¥¢¥¦¥ÈÀ߷פǤϡ¢¤·¤Ð¤·¤ÐÊ£¿ô¤Î¥»¥ëÂФò¼´¤ËÂФ·¤ÆÀþÂоΤËÇÛÃÖ¤¹¤ë¤³¤È¤¬Í׵ᤵ¤ì¤ë¡£Balasa¤é¤Ï¤É¤ó¤Êº¸²¼µÍ¤áÇÛÃÖ¤âɽ¤¹¤³¤È¤¬¤Ç¤¤ëO-tree¤òÍѤ¤¤ÆÂоÎÇÛÃÖÀ©Ì󲼤ǤÎÇÛÃÖ¼êË¡¤òÄó°Æ¤·¤¿¡£ ¤·¤«¤·¤³¤Î¼êË¡¤Ç¤ÏÆþÎϤµ¤ì¤¿O-tree¤ÎÀ©Ìó¤òËþ¤¿¤µ¤Ê¤¤ÇÛÃÖ¤¬ÆÀ¤é¤ì¤¿¤ê¡¢À©Ìó¤òËþ¤¿¤·¤Æ¤¤¤Æ¤âºÇÌ©¤Ç¤Ê¤¤ÇÛÃÖ¤¬ÆÀ¤é¤ì¤ëÅù¤Î·ç´Ù¤¬¤¢¤ë¡£ ¤½¤³¤ÇËܹƤǤÏO-tree¤ÎÀ©Ìó¤ÈÂоÎÇÛÃÖÀ©Ìó¤Ï¶¦¤ËÀþ·Á¤Ê¼°¤ËÊÑ´¹¤Ç¤¤ë¤³¤È¤òÍøÍѤ·¡¢¹ÃÅĤé¤Ë¤è¤ësequence-pair¤òÍѤ¤¤¿¼êË¡¤ÈƱÍͤËÀ©Ì󲼤ǺÇÌ©¤ÊÇÛÃÖ¤òÀþ·Á·×²èË¡¤òÍѤ¤¤ÆÆÀ¤ë¼êË¡¤òÄó°Æ¤¹¤ë¡£ |
Âê̾ | Éô²°¤ÎÎÙÀÜ´Ø·¸¤ò´Þ¤ó¤À½çÎó¤È¥Õ¥í¥¢¥×¥é¥ó¤ÎÂбþ |
Ãø¼Ô | ¡ûÆ£´¬ μ, ¹â¶¶ ½Óɧ(¿·³ãÂç³ØÂç³Ø±¡¼«Á³²Ê³Ø¸¦µæ²Ê) |
Page | pp. 247 - 252 |
Keyword | ¥Õ¥í¥¢¥×¥é¥ó, ɽ¸½Ë¡, ½çÎó, ÎÙÀÜ´Ø·¸ |
Abstract | ¥Õ¥í¥¢¥×¥é¥ó¤È¤Ï¶ë·Á¤ò¿åÊ¿Àþʬ¤ª¤è¤Ó¿âľÀþʬ¤Ë¤è¤ê¡¢´ö¤Ä¤«¤Î¶ë·Á¤ØºÙʬ¤·¤¿¤â¤Î¤Ç¤¢¤ë¡£¤³¤ì¤Þ¤Ç¤ËVLSI¥ì¥¤¥¢¥¦¥ÈÀ߷פʤɤؤαþÍѤ«¤é¡¢ÍÍ¡¹¤Ê¥Õ¥í¥¢¥×¥é¥ó¤Îɽ¸½Ë¡¤¬Äó°Æ¤µ¤ì¤¿¡£·×»»µ¡¤Ë¤è¤Ã¤Æ¥Õ¥í¥¢¥×¥é¥ó¤ò¼è¤ê°·¤¦¾ì¹ç¡¢¤½¤Îɽ¸½Ë¡¤Ï¤Ç¤¤ë¤À¤±´Êñ¤Ç¤¢¤ê¡¢°·¤¤¤ä¤¹¤¤¤³¤È¤¬Ë¾¤Þ¤ì¤ë¡£¶áǯ¤Î¸¦µæ¤Ë¤è¤ê¡¢Éô²°Æ±»Î¤ÎÎÙÀÜ´Ø·¸¤ò¹Íθ¤·¤Ê¤¤¾ì¹ç¤Ë¤Ï¡¢nÉô²°¤Î¥Õ¥í¥¢¥×¥é¥ó¤òn-½çÎó¤È¤¤¤¦´Êñ¤Ê¹½Â¤¤Çɽ¸½¤Ç¤¤ë¤³¤È¤¬¼¨¤µ¤ì¤¿¡£ËÜÊó¹ð¤Ï¡¢Éô²°Æ±»Î¤ÎÎÙÀÜ´Ø·¸¤ò¹Íθ¤·¤¿¥Õ¥í¥¢¥×¥é¥ó¤Ç¤â¡¢Æ±¤¸¤¯n-½çÎó¤Ë¤è¤Ã¤Æɽ¸½¤Ç¤¤ë¤³¤È¤ò¼¨¤¹¡£¤µ¤é¤Ë¡¢Äó°Æ¤¹¤ëɽ¸½Ë¡¤ÏÈóµöÍÆɽ¸½¤ò»ý¤¿¤Ê¤¤¡¢¤¹¤Ê¤ï¤ÁǤ°Õ¤În-½çÎó¤¬nÉô²°¤Î¥Õ¥í¥¢¥×¥é¥ó¤ËÂбþ¤¹¤ë¤È¤¤¤¦Ãµº÷¥¢¥ë¥´¥ê¥º¥à¤ËŬ¤·¤¿À¼Á¤òÈ÷¤¨¤Æ¤¤¤ë¡£ |
Âê̾ | ÀÞ¤ì¶Ê¤¬¤ê¤Èʬ´ô¤òµöÍƤ·¤¿¥Ð¥¹¥É¥ê¥Ö¥ó¥Õ¥í¥¢¥×¥é¥óÀß·×¼êË¡ |
Ãø¼Ô | ¡ûÊ¿ÎÉ ÍÎÍ´, Æ£µÈ Ë®ÍÎ(ÅìµþÇÀ¹©Âç³Ø ) |
Page | pp. 253 - 258 |
Keyword | ¥Õ¥í¥¢¥×¥é¥ó, ¥Ð¥¹, ¥Ó¥¢, sequence-pair |
Âê̾ | ¥ì¥¸¥¹¥¿¤ÎºÆÇÛÃ֤ˤè¤ë½àƱ´ü¼°²óÏ©¤Î¥¯¥í¥Ã¥¯¼þ´üºÇ¾®²½¼êË¡ |
Ãø¼Ô | ¡û¾®Ê¿ ¹Ô½¨, ¹â¶¶ ÆÆ»Ê(Åìµþ¹©¶ÈÂç³ØÂç³Ø±¡ Íý¹©³Ø¸¦µæ²Ê ½¸ÀÑ¥·¥¹¥Æ¥àÀ칶) |
Page | pp. 259 - 264 |
Keyword | ½àƱ´üÊý¼°, ¥ì¥¸¥¹¥¿¤ÎºÆÇÛÃÖ, ¥ê¥¿¥¤¥ß¥ó¥° |
Abstract | ½àƱ´üÊý¼°¤Ç¤Ï¥¯¥í¥Ã¥¯¥¿¥¤¥ß¥ó¥°¤òÊѹ¹¤¹¤ë¤³¤È¤Ë¤è¤êºÇ¾®¥¯¥í¥Ã¥¯¼þ´ü¤ò²¼¤²¤é¤ì¤ë²ÄǽÀ¤¬¤¢¤ë¤¬¡¤ºÇ¾®¥¯¥í¥Ã¥¯¼þ´ü¤Î²¼³¦¤òãÀ®¤Ç¤¤ë¤È¤Ï¸Â¤é¤Ê¤¤¡¥°ìÊý¡¤´°Á´Æ±´üÊý¼°¤Ë¤ª¤±¤ë¥ì¥¸¥¹¥¿¤ÎºÆÇÛÃ֤ǤÏÃÙ±äÃͤòǤ°Õ¤ÎÃͤËʬ³ä¤Ç¤¤ë¤È¤¡¤ºÇ¾®¥¯¥í¥Ã¥¯¼þ´ü¤Î²¼³¦¤òãÀ®¤Ç¤¤ë¤¬¡¤ÃÙ±äÃͤòǤ°Õ¤ÎÃͤËʬ³ä¤Ç¤¤ë¤È¤¤¤¦¾ò·ï¤Ï¸½¼ÂŪ¤Ç¤Ï¤Ê¤¤¡¥ÃÙ±äÃͤòʬ³ä¤Ç¤¤Ê¤¤¤È¤¤Ï¡¤¸Â³¦ºÇ¾®¥¯¥í¥Ã¥¯¼þ´ü¤òãÀ®¤Ç¤¤ë¤È¤Ï¸Â¤é¤Ê¤¤¡¥¤½¤³¤ÇËܹƤǤϡ¤³ÆÃÙ±äÁǻҤ¬°ì°Õ¤ÎÃÙ±äÃͤòͤ·¤Æ¤¤¤ë¤È¤¤¤¦¾ò·ï¤Î²¼¤Ç¡¤ÃÙ±äÁǻҤòʬ³ä¤¹¤ë¤³¤È¤Ê¤¯¡¤½àƱ´üÊý¼°¤Ë¤ª¤±¤ë¥ì¥¸¥¹¥¿¤ÎºÆÇÛÃ֤ˤè¤êºÇ¾®¥¯¥í¥Ã¥¯¼þ´ü¤Î²¼³¦¤ò¼Â¸½¤¹¤ë¹â®¤Ê¼êË¡¤òÄó°Æ¤¹¤ë¡¥ |
Âê̾ | 3¼¡¸µ¥¹¥é¥¤¥¹¹½Â¤¤Ë¤ª¤±¤ëľÊýÂβóž¤Ë¤è¤ëÂÎÀѺǾ®²½¼êË¡ |
Ãø¼Ô | ¡ûÀи¶ ·¼Í´, Æ£µÈ Ë®ÍÎ(ÅìµþÇÀ¹©Âç³ØÂç³Ø±¡ Åŵ¤ÅŻҹ©³ØÀ칶) |
Page | pp. 265 - 270 |
Keyword | ľÊýÂΥѥå¥ó¥°, ÂÎÀѺǾ®²½, Ê»¹çÁàºî |
Âê̾ | (¾·ÂÔ)VDEC¤Î¤³¤ì¤Þ¤Ç¤Î10ǯ¤Èº£¸å¤ÎŸ³« |
Ãø¼Ô | ¡ûÀõÅÄ Ë®Çî(ÅìµþÂç³ØÂ絬ÌϽ¸ÀÑ¥·¥¹¥Æ¥àÀ߷׶µ°é¸¦µæ¥»¥ó¥¿¡¼) |
Page | pp. 271 - 276 |
Keyword | LSI¶µ°é, ¥Á¥Ã¥×»îºî, CAD¥Ä¡¼¥ë, Àß·×¥»¥ß¥Ê, VDEC |
Abstract | VDEC¤¬1996ǯ5·î¤Ëȯ¤·¤Æ10ǯ¤¬·Ð²á¤·¤¿¡£¤³¤ì¤Þ¤ÇLSIÀß·×´ðÈ׳ÎΩ¤Î¤¿¤á¡ËܳÊŪÀ߷ץġ¼¥ëÀ°È÷¢Âç³Ø¸¦µæ¶µ°é¥³¥¹¥È¤Ë¸«¹ç¤¦LSI¥Á¥Ã¥×»îºî¥·¥¹¥Æ¥à¹½ÃÛ£¥»¥ß¥Ê¡¼¡¦¥È¥ì¡¼¥Ë¥ó¥°³«ºÅ¡¢Åù¤ò¹Ô¤Ã¤Æ¤¤¿¡£¤Þ¤¿ºÇ¶È³¦¤Î¶¨ÎϤβ¼¡¢VDEC¥æ¡¼¥¶¤¬¶¦Ä̤ËÍøÍѤǤ¤ëÀ߷ץ饤¥Ö¥é¥ê¡¿IP¥³¥¢¤ÎÀ°È÷¤ËÅؤᡢ¼ã¼ê¸¦µæ¼Ô¤ÎÍ¥¤ì¤¿LSIÀß·×¥×¥í¥¸¥§¥¯¥È¤ò»Ù±ç¤¹¤ë¤¿¤á¤Î¤µ¤Þ¤¶¤Þ¤Ê»ÅÁȤߤò¹½ÃÛ¤·¤Æ¤¤¿¡£²áµî10ǯ´Ö¤ÎÃæ¤ÇÂç³Ø¤ÏË¡¿Í²½¤·¡¢¼è¤ê´¬¤¯´Ä¶¤ÏÂ礤¯ÊѤï¤Ã¤¿¤¬¡¢ËܹƤǤÏVDEC10ǯ¤Î³èÆ°¤òÁí³ç¤·¡¢º£¸å¤Î³èÆ°Êý¿Ë¤Ë¤Ä¤¤¤Æ¹Í¤¨¤ò½Ò¤Ù¤¿¤¤¡£ |
Âê̾ | ´Ö·ç¼Â¹Ô¥í¥°¤«¤é¤Î¥×¥í¥°¥é¥à¤Î¼Â¹Ô·ÐÏ©¿äÄê¼êË¡¤ÎÄó°Æ |
Ãø¼Ô | ¡ûÂçÄÐ ÃλË((³ô)Åì¼Ç ¸¦µæ³«È¯¥»¥ó¥¿¡¼), Ì³À ľ¹À((³ô)Åì¼Ç¥»¥ß¥³¥ó¥À¥¯¥¿¡¼¼Ò SoC¸¦µæ³«È¯¥»¥ó¥¿¡¼), °¦¿Ü ±ÑÇ·((³ô)Åì¼Ç ¸¦µæ³«È¯¥»¥ó¥¿¡¼) |
Page | pp. 277 - 282 |
Keyword | ¥×¥í¥Õ¥¡¥¤¥ë, ¼Â¹Ô¥í¥°, ¥¢¥ë¥´¥ê¥º¥à |
Abstract | ¥×¥í¥°¥é¥à¤ÎÀǽ¥Á¥å¡¼¥Ë¥ó¥°¤Î¤¿¤á¤Î¥×¥í¥Õ¥¡¥¤¥ë¥Ä¡¼¥ë¤È¤·¤Æ¡¢¤¿¤È¤¨¤Ðunix¤Ê¤É¤Ç»ÈÍѤµ¤ì¤ëgprofÅù¤¬¤è¤¯ÃΤé¤ì¤Æ¤¤¤ë¡£¤·¤«¤·¡¢½¾Íè¤Î¥×¥í¥Õ¥¡¥¤¥ë¥Ä¡¼¥ë¤Ï¡¢¥³¥ó¥Ñ¥¤¥ë»þ¤Ë¡¢¥½¡¼¥¹¥³¡¼¥É¤Ë¥×¥í¡¼¥Ö¤òÁÞÆþ¤¹¤ë¿¯½±Êý¼°¤Ç¤¢¤ê¡¢¥½¡¼¥¹¥³¡¼¥É¤¬É¬¿Ü¤Ç¤¢¤ë¡£¤Þ¤¿¡¢¥×¥í¡¼¥ÖÁÞÆþ¤Ë¤è¤ë¾ñÍð¤¬ÌäÂê¤È¤Ê¤ë¡£¤½¤³¤ÇËܹƤǤϡ¢½¾Íè¤Î¿¯½±Êý¼°¤È¤Ï°Û¤Ê¤ê¡¢¼Â¹Ô»þ¤ÎÆ°ºî¤ò³°Éô¤«¤é´Æ»ë¤¹¤ë¤³¤È¤Ë¤è¤ê¼Â¹Ô¾ðÊó¤òÆÀ¤ëÈ󿯽±Êý¼°¤Î¥×¥í¥Õ¥¡¥¤¥ë¤òÄó°Æ¤¹¤ë¡£È󿯽±Êý¼°¤Î¥×¥í¥Õ¥¡¥¤¥ë¤Ç¤Ï¡¢¿¯½±Êý¼°¤Î¥×¥í¥Õ¥¡¥¤¥ë¤È¤Ï°Û¤Ê¤ê¡¢¥½¡¼¥¹¥³¡¼¥É¾å¤Ë¥í¥°¼èÆÀ°ÌÃÖ¤ò»ØÄê¤Ç¤¤Ê¤¤¤¿¤á¡¢¼ý½¸¤·¤¿¼Â¹Ô¥í¥°¤Î¥Ç¡¼¥¿¤«¤é¡¢¥×¥í¥°¥é¥à¤Î¼Â¹Ô·ÐÏ©¤ò¿äÄꤹ¤ëɬÍפ¬¤¢¤ë¡£¤½¤³¤Ç¡¢ËܹƤǤϡ¢¥×¥í¥°¥é¥à¤Î¼Â¹Ô»þ¤Î´Ö·ç¥í¥°¤«¤é¥×¥í¥°¥é¥à¤Î¼Â¹Ô·ÐÏ©¤ÎÈϰϤò¿äÄꤹ¤ë¥¢¥ë¥´¥ê¥º¥à¤òÄó°Æ¤·¡¢¤½¤Î¸¡¾Ú·ë²Ì¤Ë´Ø¤·¤Æ½Ò¤Ù¤ë¡£ |
Âê̾ | A Tableau Construction for Control Synthesis of FSMs |
Ãø¼Ô | ¡ûYoshisato Sakai(Toshiba Corporation) |
Page | pp. 283 - 288 |
Keyword | temporal logic, tableau, control synthesis, formal method |
Abstract | We propose a tableau construction in the form of FSM instead of Kripke structure, and show a method to synthesize controllers for FSMs using the tableaus. This method accepts a formula of ASTL (a kind of temporal logic) as a specification of desired behaviors of the system. The model of a plant (component to be controlled) is given as an FSM, which can be a synchronous circuit. |
Âê̾ | ¥¤¥ó¥¿¡¼¥ï¡¼¥¯¥Õ¥í¡¼¤Î¥ï¡¼¥¯¥Õ¥í¡¼¥Í¥Ã¥È¥â¥Ç¥ë¤È¤½¤Î·òÁ´À¤Ë¤Ä¤¤¤Æ |
Ãø¼Ô | ¡û»³¸ý ¿¿¸ç(»³¸ýÂç³ØÂç³Ø±¡/Íý¹©³Ø¸¦µæ²Ê), ¾¾Èø Âç(ÂçÆüËÜ°õºþ(³ô)), ³ë ºê°Î(»³¸ýÂç³Ø/¶µ°é³ØÉô), ÅÄÃæ Ì(»³¸ýÂç³ØÂç³Ø±¡/Íý¹©³Ø¸¦µæ²Ê) |
Page | pp. 289 - 294 |
Keyword | ¥ï¡¼¥¯¥Õ¥í¡¼, ¥¤¥ó¥¿¡¼¥ï¡¼¥¯¥Õ¥í¡¼, ¥Ú¥È¥ê¥Í¥Ã¥È, ·òÁ´À, WfMC |
Abstract | ËܹƤǤϥ¤¥ó¥¿¡¼¥ï¡¼¥¯¥Õ¥í¡¼¤Î¥ï¡¼¥¯¥Õ¥í¡¼(WF)¥Í¥Ã¥È¥â¥Ç¥ë¤È¤½¤Î·òÁ´À¤Ë¤Ä¤¤¤ÆµÄÏÀ¤¹¤ë¡£¤Þ¤º¥¤¥ó¥¿¡¼¥ï¡¼¥¯¥Õ¥í¡¼¤Îɸ½à¥×¥í¥È¥³¥ë¤ÇÄê¤á¤é¤ì¤¿3¼ïÎà¤ÎÏ¢·È·¿¤Î¤½¤ì¤¾¤ì¤ËÂФ·¤ÆWF¥Í¥Ã¥È¤Ë¤è¤ë¥â¥Ç¥ë²½¤ò¼¨¤¹¡£Ç¤°Õ¤Î¥¤¥ó¥¿¡¼¥ï¡¼¥¯¥Õ¥í¡¼¤Ï¤½¤ì¤é¤òÁȤ߹ç¤ï¤»¤ë¤³¤È¤Ë¤è¤Ã¤Æ¥â¥Ç¥ë²½¤Ç¤¤ë¡£¼¡¤Ë¡¢Ç¤°Õ¤Î¥¤¥ó¥¿¡¼¥ï¡¼¥¯¥Õ¥í¡¼¤ò¥â¥Ç¥ë²½¤·¤¿WF¥Í¥Ã¥È¤¬¤É¤Î¤è¤¦¤Ê¥¯¥é¥¹¤Ë¤Ê¤ë¤«¤òÌÀ¤é¤«¤Ë¤¹¤ë¡£¤½¤·¤Æ¡¢¤½¤Î¥µ¥Ö¥¯¥é¥¹¤´¤È¤Ë¡¢¤½¤Î·òÁ´À¤Ë¤Ä¤¤¤ÆµÄÏÀ¤·¡¢ºÇ¸å¤Ë¥¤¥ó¥¿¡¼¥ï¡¼¥¯¥Õ¥í¡¼¤Î»öÎ㤬Àµ¾ï¤Ë½ªÎ»¤¹¤ë¤«¤É¤¦¤«¤ò¸¡ºº¤¹¤ëÎã¤ò¼¨¤¹¡£ |
Âê̾ | (¾·ÂÔ)Extended Skip Graph for P2P File Exploration |
Ãø¼Ô | ¡ûÆ£ÅÄ Áï(¹ÅçÂç³ØÂç³Ø±¡ ¹©³Ø¸¦µæ²Ê ¾ðÊ󹩳ØÀ칶) |
Page | pp. 295 - 300 |
Keyword | P2P, ¥ª¡¼¥Ð¡¼¥ì¥¤¥Í¥Ã¥È¥ï¡¼¥¯, ¥¹¥¥Ã¥×¥°¥é¥Õ |
Abstract | ËܹƤǤϡ¤³Æ¥Î¡¼¥É¤ÎÊ¿¶Ñ¼¡¿ô¤¬Äê¿ô¤Ç¡¤¤·¤«¤â¿¹àÂпô»þ´Ö¤Ç¤Î¥¯¥¨¥ê¤Î¥ë¡¼¥Æ¥£¥ó¥°¤ò²Äǽ¤È¤¹¤ë¤è¤¦¤Ê¡¤P2P¥·¥¹¥Æ¥à¤Î¤¿¤á¤Î¿·¤·¤¤¹½Â¤·¿¥ª¡¼¥Ð¡¼¥ì¥¤¥Í¥Ã¥È¥ï¡¼¥¯¤ÎÄó°Æ¤ò¹Ô¤¦¡¥Äó°Æ¤¹¤ë¥ª¡¼¥Ð¡¼¥ì¥¤¥Í¥Ã¥È¥ï¡¼¥¯¤Ï¡¤¥¹¥¥Ã¥×¥°¥é¥Õ¤Î³ÈÄ¥¤Ç¤¢¤ê¡¢¥¹¥¥Ã¥×¥°¥é¥Õ¤ÇÍѤ¤¤é¤ì¤Æ¤¤¤¿¥Î¡¼¥É¤¢¤¿¤êO(log N)ËܤΥ·¥ç¡¼¥È¥«¥Ã¥È¥ê¥ó¥¯¤Î¤¦¤Á¡¤Äê¿ôËܤΤߤò¥é¥ó¥À¥à¤ËÁªÂò¤¹¤ë¤³¤È¤Ç¡¤O(log^2 N)¥¹¥Æ¥Ã¥×¤ÎÊ¿¶Ñ¥ë¡¼¥Æ¥£¥ó¥°»þ´Ö¤ò¼Â¸½¤¹¤ë¡¥ |
Âê̾ | (¾·ÂÔ)An Experimental Study of the Webgraph |
Ãø¼Ô | ¡û±§Ìî ͵Ƿ, ÂçÅÄ µÁ¿®, ¾åÆ» ÌÀÀ¸, ÇÏÌî ¸µ½¨(ÂçºåÉÜΩÂç³Ø Íý³Ø·Ï¸¦µæ²Ê ¾ðÊó¿ôÍý²Ê³ØÀ칶) |
Page | pp. 301 - 306 |
Keyword | link analysis, scale-free network, webgraph, web community, web structure mining |
Abstract | The link structure of the Web is generally viewed as the webgraph. Web structure mining is a research area that aims to find hidden communities in the Web based on the webgraph, and communities or their cores are supposed to constitute dense subgraphs. Then, structure mining is realized by enumerating those substructures. In this paper, we focus on bicliques, cliques and isolated cliques as such candidate substructures, and attempt to investigate properties of the webgraph and to find useful information from the real web data. As a result, we observed several interesting structural properties of the Web. Furthermore, we discovered that isolated cliques can be quite useful for detecting harmful link farms, while isolated cliques that lie over multiple domains sometimes stand for useful communities, which implies the validity of isolated cliques in web structure mining. |
Âê̾ | (¾·ÂÔ)The Weakest Failure Detectors for Solving the Stable Leader Election |
Ãø¼Ô | ¡ûHirotaka Ono(Department of Computer Science and Communication Science, Kyushu University), Sung Hoon Park(School of Electrical and Computer Engineering, Chungbuk National University), Masafumi Yamashita(Department of Computer Science and Communication Science, Kyushu University) |
Page | pp. 307 - 312 |
Keyword | Weakest Failure Detectors, Stable Leader Election, Consensus, Fault- |
Âê̾ | (¾·ÂÔ)¡Ö²ÁÃ͡פȡֿ®Íѡפò¼è¤ê°·¤¦¾ðÊ󵻽Ѥ˸þ¤±¤Æ |
Ãø¼Ô | ¡û°Â±º ´²¿Í(¶å½£Âç³Ø) |
Page | pp. 313 - 318 |
Âê̾ | ºÇŬ¾õÂÖ³°¤Ë¤ª¤±¤ëDEµéÁýÉý´ï¤ÎÆ°ºî²òÀÏ |
Ãø¼Ô | º¬´ß ¹â¹°, ¡û´Ø²° Âçͺ, Ϥ ·úÌÀ, ëÇë δ»Ì(ÀéÍÕÂç³Ø) |
Page | pp. 319 - 324 |
Keyword | ²óÏ©²òÀÏ, ÁýÉý´ï |
Abstract | ËÜÏÀʸ¤Ç¤Ï, ºÇŬ¾õÂÖ³°¤Ë¤ª¤±¤ëDEµéÁýÉý´ï¤ÎÆ°ºî²òÀϤò¹Ô¤¦. ÍÍ¡¹¤ÊÀß·×»ÅÍͤËÂбþ¤·¤¿ DE µéÁýÉý´ï¤ÎÆ°ºî²òÀϤòãÀ®¤¹¤ë¤¿¤á¤Ë, ¶èʬÀþ·Á¤Çɽ¸½¤µ¤ì¤¿¾ïÈùʬÊýÄø¼°¤ò²ò¤¯¤³¤È¤Ë¤è¤ê²òÀϤò¹Ô¤¦. ¤³¤³¤Ç, ½¾Íè¤Î¸¦µæ¤Ç¤ÏEµéÆ°ºî¾ò·ï¤òËþ¤¿¤¹²óÏ©¤ÎÀ߷פ¬ÌÜŪ¤Ç¤¢¤ë¤¿¤á, ³Æ¶èʬ¤ÎÅÅή¤ª¤è¤ÓÅÅ°µ¤Î½é´üÃͤòÀܳ¾ò·ï¤«¤é¿ôÃÍŪ¤ËƳ½Ð¤·¤Æ¤¤¤ë¤¬, ËÜÏÀʸ¤Ç¤Ï¤½¤ì¤é¤ò²òÀÏŪ¤ËƳ½Ð¤¹¤ë. ½é´üÃͤò²òÀÏŪ¤ËƳ½Ð¤¹¤ë¤³¤È¤Ë¤è¤ê, DE µéÁýÉý´ï¤Ë¤ª¤¤¤Æ½ÅÍפʰÕÌ£¤ò»ý¤Ä¥¹¥¤¥Ã¥ÁÅÅ°µ, ¥¹¥¤¥Ã¥ÁÅÅ°µ¤Î·¹¤, ½ÐÎÏÅÅ°µ¤ª¤è¤ÓÅÅÎÏÊÑ´¹¸úΨ¤òÁ´¤Æ²òÀÏŪ¤Ëɽ¸½¤¹¤ë¤³¤È¤¬²Äǽ¤È¤Ê¤ë. Ƴ½Ð¤·¤¿²òÀϼ°¤òÍѤ¤¤ÆºÇŬ¾õÂÖ¤«¤éÆ°ºî¼þÇÈ¿ô, »þÈæΨ, ÆþÎÏÅÅ°µ, Éé²ÙÄñ¹³¤¬ÊѲ½¤·¤¿¤È¤¤Î DE µéÁýÉý´ï¤ÎÆ°ºî¤Ë¤Ä¤¤¤Æ¸¡Æ¤¤¹¤ë. ¤Þ¤¿, ²óÏ©¼Â¸³¤È¤ÎÈæ³Ó¤Ë¤è¤ê, ²òÀÏ·ë²Ì¤ÎÂÅÅöÀ¤ò¼¨¤¹. |
Âê̾ | ÊÂÎó²½Buck¥³¥ó¥Ð¡¼¥¿¤Î¥ê¥¿¡¼¥ó¥Þ¥Ã¥×¤Ë¤è¤ë²òÀÏ |
Ãø¼Ô | ¡ûÀÐÀî ͵¸Ê, ¾¾²¬ Í´²ð, ºØÆ£ ÍøÄÌ(Ë¡À¯Âç³Ø) |
Page | pp. 325 - 329 |
Keyword | ¥Ñ¥ï¡¼¥³¥ó¥Ð¡¼¥¿, Ʊ´ü, ʬ´ô |
Abstract | ¡¡ÊÂÎó²½DC/DC¥³¥ó¥Ð¡¼¥¿¤Ë¤Ä¤¤¤Æ¡¢¥ê¥¿¡¼¥ó¥Þ¥Ã¥×¤Ë¤è¤ë²òÀÏË¡¤òÄó°Æ¤¹¤ë¡£ËÜÏÀʸ¤Ç¤Ï¡¢DC/DC¥³¥ó¥Ð¡¼¥¿¤Î°ì¼ï¤Ç¤¢¤ëBuck¥³¥ó¥Ð¡¼¥¿¤ò¥â¥Ç¥ë¤È¤·¡¢WTA¤Ë´ð¤Å¤¯ÊÂÎó²½DC/DC¥³¥ó¥Ð¡¼¥¿¤ÎƱ´ü¸½¾Ý¤äʬ´ô¸½¾Ý¤ò¡¢¥ê¥¿¡¼¥ó¥Þ¥Ã¥×¤òÍѤ¤¤Æ²òÀϤ¹¤ë¡£ ¡¡¤Þ¤¿¡¢´ÊÁǤʲóÏ©¤ò»îºî¤·¡¢´ðËܸ½¾Ý¤ò¼Â¸³Åª¤Ë¸¡¾Ú¤¹¤ë¡£ |
Âê̾ | ¥Ð¥ó¥É¥Ñ¥¹¥Õ¥£¥ë¥¿¤òÍѤ¤¤¿DEµéÁýÉý´ï¤ÎÀß·× |
Ãø¼Ô | ¡ûÊÒ»³ ´´, Ĺë ¹¨Ç·, ´Ø²° Âçͺ, Ϥ ·úÌÀ, ëÇë δ»Ì(ÀéÍÕÂç³ØÂç³Ø±¡¼«Á³²Ê³Ø¸¦µæ²Ê) |
Page | pp. 331 - 336 |
Keyword | DEµéÁýÉý´ï, ¥Ð¥ó¥É¥Ñ¥¹¥Õ¥£¥ë¥¿ |
Abstract | DEµéÁýÉý´ï ¤Ï¹âÆ°ºî¼þÇÈ¿ô²¼¤Ë¤ª¤¤¤Æ¹âÅÅÎÏÊÑ´¹¸úΨ¤òãÀ®¤¹¤ëÁýÉý´ï¤Ç¤¢¤ë¡£¤·¤«¤·, DEµéÁýÉý´ï¤Ï¶¦¿¶¥Õ¥£¥ë¥¿¤òÍѤ¤¤Æ¤¤¤ë¤¿¤á, ½ÐÎÏÅÅ°µ¤¬Æ°ºî¼þÇÈ¿ô¤ÎÊÑÆ°¤ä¥Õ¥£¥ë¥¿¤ÎÁÇ»ÒÃͤΤФé¤Ä¤¤Ë±ÔÉҤǤ¢¤ë¤È¤¤¤¦ÌäÂêÅÀ¤ò¤â¤Ä. ¤Þ¤¿, Æ°ºî¼þÇÈ¿ôÊÑÆ°»þ¤Ë¤ÏEµéÆ°ºî¾ò·ï¤òËþ¤¿¤¹¤³¤È¤¬ÉÔ²Äǽ¤Ë¤Ê¤ë. Ëܸ¦µæ¤Ç¤Ï, DEµéÁýÉý´ï¤Î½ÐÎÏ¥Õ¥£¥ë¥¿¤ò¥Ð¥ó¥É¥Ñ¥¹¥Õ¥£¥ë¥¿¤È¤·¤¿DEµéÁýÉý´ï¤òÄó°Æ¤¹¤ë. ¥Ð¥ó¥É¥Ñ¥¹¥Õ¥£¥ë¥¿¤òÍѤ¤¤ë¤³¤È¤ÇÆ°ºî¼þÇÈ¿ôÊÑÆ°»þ¤Î½ÐÎÏÅÅ°µ¤ÎÊÑÆ°¤òÍÞÀ©¤Ç¤¤ë. ¤µ¤é¤Ë, Æ°ºî¼þÇÈ¿ô¤¬Ä㤯¤Ê¤Ã¤¿¾ì¹ç¤ÏµÕÊÂÎó¥À¥¤¥ª¡¼¥É¤Ë¤è¤êÎíÅÅ°µ¥¹¥¤¥Ã¥Á¥ó¥°¤òËþ¤¿¤¹¤³¤È¤¬²Äǽ¤Ç¤¢¤ë. ¤Þ¤¿, ²óÏ©¼Â¸³¤ò¹Ô¤¦¤³¤È¤Ë¤è¤êÀ߷פÎÂÅÅöÀ¤ò¼¨¤¹. |
Âê̾ | (¾·ÂÔ)¥¹¥¤¥Ã¥Á¥ó¥°·Ï¤Î¥À¥¤¥Ê¥ß¥¯¥¹¤È¥Ï¥¤¥Ö¥ê¥Ã¥ÉÀ |
Ãø¼Ô | ¡û°ú¸¶ δ»Î(µþÅÔÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê) |
Page | pp. 337 - 342 |
Keyword | ¥¹¥¤¥Ã¥Á, ÀÚÂؤ¨, ÈóÀþ·Á¥À¥¤¥Ê¥ß¥¯¥¹, ¥Ï¥¤¥Ö¥ê¥Ã¥ÉÀ |
Abstract | Ϣ³¤ÊÎϳؤ˻ÙÇÛ¤µ¤ì¤¿·Ï¤¬¡¤¤¢¤ë¾ò·ï¤ÎÀ®Î©¤È¤È¤â¤Ë¾õÂÖ¥¹¥¤¥Ã¥Á¤Ë¤è¤Ã¤ÆÉÔϢ³¤Ë°Û¤Ê¤ëÎϳطϤËÁ«°Ü¤¹¤ë¥·¥¹¥Æ¥à¡¤¤¹¤Ê¤ï¤ÁϢ³¤ÊÎϳطϤÈÉÔϢ³¤Ê¾õÂÖÁ«°Ü¤ò´Þ¤à·Ï¤Ï¡¤¹©³Ø¥·¥¹¥Æ¥à¤À¤±¤Ç¤Ê¤¯¼«Á³³¦¤Ë¤â¹¤¯¸«¤é¤ì¤ë¡¥¥¹¥¤¥Ã¥Á¤Ï¡¤¾ðÊóʬÌ¤è¤Ó¥Ñ¥ï¡¼Ê¬Ìî¤Ç²óÏ©Æ°ºî¤òÀ©¸æ¤¹¤ë½ÅÍפÊÍ×ÁǤǤ¢¤ë¤¬¡¤¤½¤ÎÆ°ºîɽ¸½¤ÏÍýÁÛ¥¹¥¤¥Ã¥Á¤Ëα¤Þ¤Ã¤Æ¤¤¤ë¡¥ËÜÏÀʸ¤Ï¡¤¥¹¥¤¥Ã¥Á¤ò´Þ¤à·Ï¤Î¥À¥¤¥Ê¥ß¥¯¥¹¤ò¥¹¥¤¥Ã¥Á¤Îɽ¸½¤Èµ¡Ç½¤«¤éºÆÅÙ¸¡Æ¤¤·¡¤¥¹¥¤¥Ã¥Á¤Ëȼ¤¦·Ï¤ÎÈóÀþ·Á¥À¥¤¥Ê¥ß¥¯¥¹¤Î¥Ï¥¤¥Ö¥ê¥Ã¥ÉÀ¤òµÄÏÀ¤¹¤ë¤â¤Î¤Ç¤¢¤ë¡¥ |
Âê̾ | Durability of Affordable Neural Networks during Back Propagation Learning |
Ãø¼Ô | ¡û¾å¼ê ÍλÒ, À¾Èø ˧ʸ(ÆÁÅçÂç³Ø), Ruedi Stoop(University / ETH Zurich) |
Page | pp. 343 - 348 |
Keyword | durability, feedforward neural network, BP learning |
Abstract | In this study, we investigate the durability of the affordable neural network when some of the neurons in the hidden layer are damaged, after the learning process. By computer simulations, we confirm that the affordable neural network keeps its efficiency. We conclude that the affordable neurons exert an important influence on durability of the network. |
Âê̾ | ¼«Î§·ÏÀÑʬȯ²Ð¥«¥ª¥¹²óÏ©¤Î¥Ñ¥ë¥¹·ÏÎó½ÐÎϤˤĤ¤¤Æ |
Ãø¼Ô | ¡û°ð³À ÃÒÍÎ, ¾¾²¬ Í´²ð, ºØÆ£ ÍøÄÌ, Ä»»ô ¹°¹¬(Ë¡À¯Âç³Ø) |
Page | pp. 349 - 353 |
Keyword | ¥¹¥Ñ¥¤¥¥ó¥°¥Ë¥å¡¼¥í¥ó, ¥«¥ª¥¹, ʬ´ô |
Abstract | ËÜÏÀʸ¤Ç¤Ï¼«Î§·ÏÀÑʬȯ²Ð¥«¥ª¥¹²óÏ©¤Ë¤Ä¤¤¤Æ¹Í»¡¤¹¤ë¡£¤³¤Î²óÏ©¤Ï2¥Ý¡¼¥ÈÅÅ°µÀ©¸æÅÅή¸»¡¢2¤Ä¤Î¥¥ã¥Ñ¥·¥¿¡¢¾õÂ֤˰͸¤·¤¿¥¹¥¤¥Ã¥Á¤Ç¹½À®¤µ¤ì¤ë¡£ÀÑʬȯ²ÐÆ°ºî¤Ë¤è¤ê¡¢Â¿ºÌ¤Ê¥Ñ¥ë¥¹Îó¤ò½ÐÎϤ·¡¢¥«¥ª¥¹¤äʬ´ô¸½¾Ý¤òÄ褹¤ë¡£ ¤³¤ì¤é¤Î¸½¾Ý¤ò²òÀϤ¹¤ë¤¿¤á¤Ë¡¢É¸½à·Á¤ÎÊýÄø¼°¤òƳÆþ¤·°ì¼¡¸µ¥ê¥¿¡¼¥ó¥Þ¥Ã¥×¤òÄêµÁ¤¹¤ë¡£ ¤³¤ì¤òÍѤ¤¤Æ¡¢Åµ·¿Åª¤Ê¸½¾ÝÎã¤òÄ´¤Ù¡¢¥Ñ¥ë¥¹Îó½ÐÎϤβòÀϤò¹Ô¤¦¡£ |
Âê̾ | Ʊ´ü·¿»ö¾Ý¤Î¤¢¤ë¥Ï¥¤¥Ö¥ê¥Ã¥É¥·¥¹¥Æ¥à¤Î¥Õ¥£¡¼¥É¥Ð¥Ã¥¯À©¸æ |
Ãø¼Ô | ¡ûÅÚ¹¾ ·Ä¹¬, Ĭ ½Ó¸÷(ÂçºåÂç³ØÂç³Ø±¡´ðÁù©³Ø¸¦µæ²Ê¥·¥¹¥Æ¥àÁÏÀ®À칶¼Ò²ñ¥·¥¹¥Æ¥à¿ôÍýÎΰè) |
Page | pp. 355 - 360 |
Keyword | ¥Ï¥¤¥Ö¥ê¥Ã¥É¥ª¡¼¥È¥Þ¥È¥ó, À©¸æÉÔÊÑ, ¾õÂÖ¥Õ¥£¡¼¥É¥Ð¥Ã¥¯ |
Abstract | Silva¤ÈKrogh¤Ï, »þ´Ö¤ËƱ´ü¤¹¤ë»ö¾Ý¤ò°·¤¦¥â¥Ç¥ë¤È¤·¤Æ¥µ¥ó¥×¥ëÃÍÀ©¸æ¥Ï¥¤¥Ö¥ê¥Ã¥É¥ª¡¼¥È¥Þ¥È¥ó(SDHA)¤òÄó°Æ¤·, ¤½¤Î¸¡¾ÚË¡ ¤Ë¤Ä¤¤¤ÆµÄÏÀ¤·¤Æ¤¤¤ë. ËÜÏÀʸ¤Ç¤Ï, SDHA¤Î¾õÂÖ¥Õ¥£¡¼¥É¥Ð¥Ã¥¯¤Ë¤Ä¤¤¤ÆµÄÏÀ¤¹¤ë. ¤Þ¤º, SDHA¥â¥Ç¥ë¤Î¥»¥Þ¥ó¥Æ¥£¥¯¥¹¤È¤·¤Æ, 2¤Ä¤Î¥È¥é¥¸¥·¥ç¥ó¥·¥¹¥Æ¥à¤òÄêµÁ¤¹¤ë. ¼¡¤Ë, ¤½¤ì¤Ë´ð¤Å¤¤¤Æ ½Ò¸ì¤ÎÀ©¸æÉÔÊÑÀ¤Ë´Ø¤¹¤ëɬÍ×½½Ê¬¾ò·ï¤ò¼¨¤¹. ºÇ¸å¤Ë, Ǥ°Õ¤Î½Ò¸ì¤ËÂФ·É¬¤ººÇÂçÀ©¸æÉÔÊÑÉôʬ½Ò¸ì¤¬Â¸ºß¤¹¤ë¤³¤È¤ò¼¨¤¹. |
Âê̾ | ¶èʬÄê¿ô¥¹¥Ñ¥¤¥¥ó¥°²óÏ©¤ÎÊ£»¨¤ÊĶ°ÂÄê¼þ´ü²ò¤Ë¤Ä¤¤¤Æ |
Ãø¼Ô | ¡û¾¾²¬ Í´²ð(Ë¡À¯Âç³Ø±¡¹©³Ø¸¦µæ²ÊÅŵ¤¹©³ØÀ칶), ºØÆ£ ÍøÄÌ, Ä»»ô ¹°¹¬(Ë¡À¯Âç³Ø) |
Page | pp. 361 - 364 |
Keyword | ¥«¥ª¥¹, ʬ´ô, °ÂÄêÀ |
Abstract | ´ÊÁǤʶèʬÄê¿ô¥¹¥Ñ¥¤¥¥ó¥°²óÏ©¤Ë¤Ä¤¤¤Æ¹Í»¡¤¹¤ë¡£ Ʊ²óÏ©¤Ï¶èʬÄê¿ô¥Ù¥¯¥È¥ë¾ì¤ò¤â¤Á¶èʬÀþ·Á¤Ê¼ÌÁü¤Ë¤è¤Ã¤Æ¸·Ì©¤Ë ¸½¾Ý¤ò²òÀϤ¹¤ë¤³¤È¤¬¤Ç¤¤ë¡£²óÏ©¤Ï»þ´ÖÀ©¸æ¤µ¤ì¤ë¥¹¥¤¥Ã¥Á¤ò´Þ¤ß¡¢ Ķ°ÂÄê¼þ´ü²ò¤Ê¤É¤Î¿ºÌ¤ÊÈóÀþ·Á¸½¾Ý¤äʬ´ô¸½¾Ý¤¬Â¸ºß¤¹¤ë¡£ ¤³¤Î¸½¾Ý¤ËÂФ·¤Æ²æ¡¹¤ÏÀºÌ©¤Ê¿ôÃͼ¸³¤ò¹Ô¤Ã¤¿¡£¤½¤Î·ë²Ì¡¢Ê£»¨¤Ê Ķ°ÂÄê¼þ´ü²ò¤Ï¥Ñ¥é¥á¡¼¥¿¤ËÈó¾ï¤Ë±ÔÉÒ¤ËÊѲ½¤¹¤ë¤³¤È¤Ê¤É¤¬Ê¬¤«¤Ã¤¿¡£ |
Âê̾ | ID¥â¥Ç¥ë¤Î¥Ð¡¼¥¹¥Èȯ²Ð¤Ø¤Î³ÈÄ¥¤È¤½¤Î½¸ÀѲóÏ©²½ |
Ãø¼Ô | ¡ûËö±Ê ¿¸Ìé, ÁáÀî µÈ¹°, ÃæÅç ¹¯¼£(ÅìËÌÂç³ØÅŵ¤ÄÌ¿®¸¦µæ½ê¥Ö¥ì¥¤¥ó¥¦¥§¥¢¼Â¸³»ÜÀß/¥Ê¥Î¡¦¥¹¥Ô¥ó¼Â¸³»ÜÀß) |
Page | pp. 365 - 370 |
Keyword | ¥Ð¡¼¥¹¥Èȯ²Ð¡¤¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¥ï¡¼¥¯, ¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¥ï¡¼¥¯, ºÇŬ²½ÌäÂê |
Abstract | Inverse function Delayed(ID)¥â¥Ç¥ë¤Ï½ÐÎÏÃÙ±äÆÃÀ¤¬Æ³Æþ¤µ¤ì¤¿ ¥â¥Ç¥ë¤Ç¤¢¤ê¡¤¸ÇͤΥÀ¥¤¥Ê¥ß¥¯¥¹¤Ë¤è¤ê¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¥ï¡¼¥¯¤ÎÀǽ¤Î¸þ¾å¤µ¤»¤ë¤³¤È¤¬¤Ç¤¤ë¥â¥Ç¥ë¤Ç¤¢¤ë¡¥Hodgkin-Huxley¥â¥Ç¥ë¤ÈID¥â¥Ç¥ë¤È¤Î´Ø·¸¤ËÃåÌܤ·¡¤¥Ð¡¼¥¹¥Èȯ²Ð¸½¾Ý¤ÎºÆ¸½¤òÌÜŪ¤ËID¥â¥Ç¥ë¤Î³ÈÄ¥¤ò»î¤ß¤¿¡¥¤Þ¤¿¡¢ÆÀ¤¿¥â¥Ç¥ë¤Î¥Ð¡¼¥¹¥Èȯ²ÐÇÈ·Á¤ò¼¨¤·¤¿¡¥N-QueenÌäÂê¤ËŬÍѤ·¡¤ID¥â¥Ç¥ë¤Ë¤ª¤¤¤ÆÀǽ¤¬Äã²¼¤¹¤ë¤è¤¦¤Ê¾ì¹ç¤Ç¤â¡¤Í¥¤ì¤¿²òõº÷Àǽ¤ò»ý¤Ä¤³¤È¤¬¤ï¤«¤Ã¤¿¡¥¤³¤Î¥â¥Ç¥ë¤Î½¸ÀѲóÏ©²½¤ò¹Ô¤Ã¤¿¡¥ |
Âê̾ | »°³ÑÇÈ¥Ù¡¼¥¹¿®¹æ¤òͤ¹¤ë¥¹¥Ñ¥¤¥¥ó¥°¥Ë¥å¡¼¥í¥ó¤Ë¤Ä¤¤¤Æ |
Ãø¼Ô | ¡ûÂçë Íø¸÷, º°Ìî µÈÃË, ºØÆ£ ÍøÄÌ, Ä»»ô ¹°¹¬(Ë¡À¯Âç³Ø) |
Page | pp. 371 - 375 |
Keyword | ¥¹¥Ñ¥¤¥¥ó¥°¥Ë¥å¡¼¥í¥ó, ¥«¥ª¥¹, ʬ´ô |
Abstract | ´ÊÁǤʥ˥塼¥í¥ó¥â¥Ç¥ë¤È¤·¤ÆÃΤé¤ì¤Æ¤¤¤ë¥¹¥Ñ¥¤¥¥ó¥°¥Ë¥å¡¼¥í¥ó¤Ë»°³ÑÇÈ¥Ù¡¼¥¹¿®¹æ¤òÆþÎϤ·¤¿¥â¥Ç¥ë¤Ë¤Ä¤¤¤Æ¹Í»¡¤¹¤ë¡£¤³¤Î¥â¥Ç¥ë¤Ï¥Ù¡¼¥¹¿®¹æ¤¬Àµ¸¹ÇȤΤâ¤Î¤ÈÈæ¤Ù¤Æ²òÀϤ¬Èó¾ï¤Ë´ÊÁǤǤ¢¤ë¤È¤¤¤¦ÆÃħ¤¬¤¢¤ë¡£ ËÜÏÀʸ¤Ï¼ç¤Ë¡¢¥Ù¡¼¥¹¿®¹æ¤Ë»°³ÑÇȤòÍѤ¤¤ë¤³¤È¤ÇȯÀ¸¤¹¤ëĶ°ÂÄê¤Ê¥Ñ¥ë¥¹·ÏÎó¤Ë¤Ä¤¤¤Æ²òÀϤò¹Ô¤Ã¤¿¡£¤³¤ì¤Ï¡¢¥Ù¡¼¥¹¿®¹æ¤¬Àµ¸¹ÇȤΤȤ¤Ë¤ÏȯÀ¸¤·¤Ê¤¤¸½¾Ý¤Ç¤¢¤ë¡£ |
Âê̾ | STDP¤òƳÆþ¤·¤¿¥Ñ¥ë¥¹·Á¥Ï¡¼¥É¥¦¥§¥¢¥Ë¥å¡¼¥í¥ó¥â¥Ç¥ë¤Ë¤ª¤±¤ë°ÌÁêÍɤ餮¤ËÂФ¹¤ë¸¡Æ¤ |
Ãø¼Ô | ¡ûÎÓ Í´¸ã(ÆüËÜÂç³ØÍý¹©³Ø¸¦µæ²ÊÅŻҹ©³ØÀ칶), º´Çì ¾¡ÉÒ, ´Øº¬ ¹¥Ê¸(ÆüËÜÂç³ØÍý¹©³ØÉôÅŻҾðÊ󹩳زÊ) |
Page | pp. 377 - 382 |
Keyword | STDP, ¥Ñ¥ë¥¹·Á¥Ï¡¼¥É¥¦¥§¥¢¥Ë¥å¡¼¥í¥ó¥â¥Ç¥ë, °ÌÁêÍɤ餮, °ÌÁ꺹 |
Abstract | ¶áǯ¡¤È¯²Ð¥¿¥¤¥ß¥ó¥°¤Ë°Í¸¤·¤¿¥·¥Ê¥×¥¹²ÄÁºÀ¡¤Spike Timing Dependent synaptic Plasticity(STDP)¤¬È¯¸«¤µ¤ì¤Æ¤¤¤ë¡£STDP¤Ïȯ²Ð¥¿¥¤¥ß¥ó¥°¤ÎÁêÂдط¸¤Ë¤è¤ë³Ø½¬Â§¤Ç¤¢¤ë¤¿¤á¡¤»þ´ÖŪ¤ÊÁê´Ø´Ø·¸¤ò»ý¤Äȯ²Ð¥Ñ¥¿¡¼¥ó¤ÎÃê½ÐǽÎϤ¬´üÂԤǤ¤ë¡£ËܹƤϡ¤STDP¤òƳÆþ¤·¤¿¥Ñ¥ë¥¹·Á¥Ï¡¼¥É¥¦¥§¥¢¥Ë¥å¡¼¥í¥ó¥â¥Ç¥ë¤òÍѤ¤¥Í¥Ã¥È¥ï¡¼¥¯¤ò¹½À®¤·¡¤È¯²Ð¥¿¥¤¥ß¥ó¥°¤Î°ÌÁ꤬Íɤ餤¤À¾õÂÖ¤òÀ¸À®¤µ¤»¡¤STDP¤¬»ý¤ÄÍɤ餮¤ËËä¤â¤ì¤¿°ÌÁê¾ðÊó¤ÎÃê½ÐǽÎϤÎ͸úÀ¤Ë¤Ä¤¤¤Æ¸¡Æ¤¤ò¹Ô¤Ã¤¿¡£¤½¤Î·ë²Ì¡¤STDP¤¬»þ´ÖŪ¤ÊÍɤ餮¤ËËä¤â¤ì¤¿°ÌÁê¾ðÊó¤ò¥·¥Ê¥×¥¹¤Î·ë¹ç²Ù½Å¤Ø¤È¥Ç¥³¡¼¥É²Äǽ¤Ç¤¢¤ë¤³¤È¤ò¼¨º¶¤·¤Æ¤¤¤ë¡£ |
Âê̾ | An Effective Large Current and High Speed Laser Diode Driver Circuit Design |
Ãø¼Ô | ¡ûYun Yang, Jia Guo, Yasuaki Inoue(Waseda University) |
Page | pp. 383 - 386 |
Keyword | laser diode driver (LDD), large current, high speed, switch position modification (SPM), combination switch mode (CSM) |
Abstract | This paper describes how to realize the high performance laser diode driver (LDD) circuit design. The new effective driver sends out large current to drive the laser diode device with high speed output signal. The signal integrity (overshoot/undershoot/slew-rate) problems have also been improved by the idea of ¡ÈSwitch Position Modification (SPM)¡É. In addition, appropriate transistor size selection and circuit combination can further amend the signal waveform. Experimental results show that the proposed LDD circuit of ¡ÈCombination Switch Mode (CSM)¡É can send out large current to drive the laser diode device with high performance output signal. |
Âê̾ | ½ÐÎÏ¥¤¥ó¥Ô¡¼¥À¥ó¥¹¤ÎÄ´À°¤Ë¤è¤ë¹â®¿®¹æÅÁÁ÷ÍÑCML¥É¥é¥¤¥Ð¤ÎÄã¾ÃÈñÅÅÎÏÀß·× |
Ãø¼Ô | ¡ûµ×ÊÝÌÚ ÌÔ, ÅÚë μ, ¾®Ìî»û ½¨½Ó(µþÅÔÂç³Ø¾ðÊó³Ø¸¦µæ²ÊÄÌ¿®¾ðÊó¥·¥¹¥Æ¥àÀ칶) |
Page | pp. 387 - 392 |
Keyword | CML, ÄãÅÅÎÏ |
Abstract | ËܹƤǤϡ¤¥ª¥ó¥Á¥Ã¥×¹â®¿®¹æÅÁÁ÷ÍÑCML¥É¥é¥¤¥Ð¤ÎÄã¾ÃÈñÅÅÎϲ½¤Ë¤Ä¤¤¤ÆµÄÏÀ¤¹¤ë¡¥½¾Í衤ÅÁÁ÷ÀþÏ©¤Î¶îÆ°²óÏ©¤Ï¥¤¥ó¥Ô¡¼¥À¥ó¥¹À°¹ç¤òÁ°Äó¤È¤·¤ÆÀ߷פ¹¤ë¤Î¤¬°ìÈÌŪ¤Ç¤¢¤ë¡¥¤·¤«¤·¡¤¥ª¥ó¥Á¥Ã¥×¤Ç¤ÏÀþÏ©¤Î¸º¿ê¤¬Â礤¤¤¿¤á¡¤ÉÔÀ°¹ç¤Ë¤è¤ëÈ¿¼Í¤¬È¯À¸¤·¤Æ¤âÀǽ¤Ë¿¼¹ï¤Ê±Æ¶Á¤òÍ¿¤¨¤Ê¤¤¡¥Äó°Æ¼êË¡¤Ç¤Ï¤³¤ÎÀ¼Á¤òÍøÍѤ·¡¤½ÐÎÏÄñ¹³¤òÆÃÀ¥¤¥ó¥Ô¡¼¥À¥ó¥¹¤è¤ê¤â¹â¤¯À߷פ¹¤ë¤³¤È¤Ç¡¤¥É¥é¥¤¥Ð¤ÎÄã¾ÃÈñÅÅÎϲ½¤ò¼Â¸½¤¹¤ë¡¥¼Â¸³¤Ë¤è¤ê¡¤ÂÓ°è¤ÎÄã²¼ 2.9%¤Ç¡¤Ìó13%¤ÎÅÅÎϺ︺¤¬²Äǽ¤Ç¤¢¤ë¤³¤È¤ò³Îǧ¤·¤¿¡¥ |
Âê̾ | ¥ª¥ó¥Á¥Ã¥×ŵ÷Î¥¹â®¿®¹æÅÁÁ÷¤ÎÀǽͽ¬ |
Ãø¼Ô | ¡ûÅÚë μ, ¾®Ìî»û ½¨½Ó(µþÅÔÂç³Ø) |
Page | pp. 393 - 398 |
Keyword | CML, ¹â®¿®¹æÅÁÁ÷, Àǽͽ¬ |
Abstract | ËܹƤǤϡ¤¥ª¥ó¥Á¥Ã¥×ŵ÷Î¥¹â®¿®¹æÅÁÁ÷¤ÎÀǽͽ¬¤Ë¤Ä¤¤¤ÆµÄÏÀ¤¹¤ë¡¥ ¥Á¥Ã¥×Æâ¤Î¿®¹æÅÁÁ÷¤Ï½ÅÍ×ÅÙ¤òÁý¤·¤Æ¤ª¤ê¡¤ ¤½¤ÎÀǽ¸«ÀѤ굻½Ñ¤Ï¥Á¥Ã¥×¤ÎÀ߷פˤª¤¤¤Æ½ÅÍפǤ¢¤ë¡¥ ¤·¤«¤·¡¤¿®¹æÅÁÁ÷·Ï¤ÎÀǽ¤Ï¥È¥é¥ó¥¸¥¹¥¿¤ÎÆÃÀ¡¤ÇÛÀþ¤ÎÆÃÀ¤ÎξÊý¤ò ¹Íθ¤¹¤ëɬÍפ¬¤¢¤ê¡¤¤¢¤ë¾ò·ï¤¬Í¿¤¨¤é¤ì¤¿¾ì¹ç¤Ë ¤É¤ÎÄøÅÙ¤ÎÅÁÁ÷®ÅÙ¤ò¼Â¸½¤Ç¤¤ë¤«¤ÏÌÀ¤é¤«¤Ç¤Ï¤Ê¤¤¡¥ ËܹƤǤϡ¤¶Ë¤Î°ÌÃÖ¤òÍѤ¤¤¿ CML¥É¥é¥¤¥Ð¤ÎÂӰ踫ÀѤê¤òÄó°Æ¤·¡¤ ´û¤ËÄó°Æ¤µ¤ì¤Æ¤¤¤ëÇÛÀþ¤ÎÀǽͽ¬¤È¹ç¤ï¤»¤Æ ¿®¹æÅÁÁ÷·Ï¤ÎÀǽͽ¬¤ò¼Â¸½¤·¤¿¡¥ ºÇÂçÅÁÁ÷®ÅÙ¤ÈÇÛÀþĹ¤Î´Ø·¸¤Ë¤Ä¤¤¤Æɾ²Á¤ò¹Ô¤Ê¤¤¡¤ ²òÀÏŪ¤Ê¸«ÀѤ꤬ÂÅÅö¤Ç¤¢¤ë¤³¤È¤ò¼Â¸³Åª¤Ë³Îǧ¤·¤¿¡¥ |
Âê̾ | ÊÂÎóÀܳ·¿¥¹¥¤¥Ã¥Á¥È¥¥ã¥Ñ¥·¥¿£Ä£Ã¡Ý£Ä£ÃÊÑ´¹²óÏ©¤Î°ìÀß·× |
Ãø¼Ô | ¡û¹¾¸ý ·¼(·§ËÜÅÅÇȹ©¶È¹âÅùÀìÌç³Ø¹»¡¿ÅŻҹ©³Ø²Ê), ÂçÅÄ °ìϺ(·§ËÜÅÅÇȹ©¶È¹âÅùÀìÌç³Ø¹»¡¿¾ðÊóÄÌ¿®¹©³Ø²Ê) |
Page | pp. 399 - 404 |
Keyword | £Ä£Ã¡Ý£Ä£Ã¥³¥ó¥Ð¡¼¥¿, ¥¹¥¤¥Ã¥Á¥È¥¥ã¥Ñ¥·¥¿²óÏ©, Î¥»¶»þ´Ö²óÏ© |
Abstract | ËÜÏÀʸ¤Ë¤ª¤¤¤Æ¤Ï¡¢ÄãÅÅ°µ¡¦ÂçÅÅή¤ò¶¡µë¤Ç¤¤ë¹ß°µ·Á£Ä£Ã¡Ý£Ä£ÃÅÅ°µÊÑ´¹²óÏ©¤ò¥¹¥¤¥Ã¥Á¥È¥¥ã¥Ñ¥·¥¿µ»½Ñ¤òÍѤ¤¤ÆÀ߷פ·¤Æ¤¤¤ë¡£Äó°Æ²óÏ©¤Ï¡¢£²¡¿£³Çܤι߰µÊÑ´¹¤ò¹Ô¤¦¥³¥ó¥Ð¡Ý¥¿¥Ö¥í¥Ã¥¯¤ò£Î¡Ê¡á£²¡¤£³¡¤Ž¥Ž¥Ž¥¡Ë¸ÄÊÂÎó¤ËÀܳ¤¹¤ë¤³¤È¤Ç¼Â¸½¤µ¤ì¤Æ¤ª¤ê¡¢ÄãÅÅ°µ¡¦ÂçÅÅή¤ò¶¡µë¤Ç¤¤ë¡£Äó°Æ²óÏ©¤Ë¤Ä¤¤¤Æ¤Ï¡¢ÍýÏÀ²òÀϤˤè¤êÊÂÎóÀܳ¿ô¤ËÂФ¹¤ëÊÑ´¹¸úΨ¤ä½ÐÎÏ¥ê¥×¥ë¤òÌÀ¤é¤«¤Ë¤·¤Æ¤¤¤ë¡£¤Þ¤¿¡¢²óÏ©À߷פÈÍýÏÀ²òÀϤÎÂÅÅöÀ¤Ë¤Ä¤¤¤Æ¡¢²óÏ©¥·¥ß¥å¥ì¡¼¥¿SPICE ¤Ë¤è¤ë¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤ò²ð¤·¤Æ³Îǧ¤·¤Æ¤¤¤ë¡£²óÏ©¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤Î·ë²Ì¤Ï¡¢ÍýÏÀ²òÀϤηë²Ì¤ÈƱ¤¸¤¯¡¢ÊÂÎóÀܳ¿ô¤òÁý²Ã¤·¤¿¾ì¹ç¤Ë¤Ï¹âÉé²Ù»þ¤Ë¤ª¤¤¤Æ¸úΨ¤¬¸º¾¯¤¹¤ë¤¬¡¢¥ê¥×¥ë¤òÄ㸺¤Ç¤¤ë¤³¤È¤ò¼¨¤·¤¿¡£ |
Âê̾ | ¥µ¥Ö¥¹¥ì¥Ã¥·¥ç¥ë¥ÉMOS LSI¤Î¤¿¤á¤Î¥¹¥¤¥Ã¥Á¥È¥¥ã¥Ñ¥·¥¿·¿DC-DC¥³¥ó¥Ð¡¼¥¿ |
Ãø¼Ô | ¡û×¢À¥ ůÌé, Àõ°æ ůÌé, ±«µÜ ¹¥¿Î(Ë̳¤Æ»Âç³Ø/Âç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê) |
Page | pp. 405 - 410 |
Keyword | ¥¹¥¤¥Ã¥Á¥È¥¥ã¥Ñ¥·¥¿, DC-DC¥³¥ó¥Ð¡¼¥¿, ¥µ¥Ö¥¹¥ì¥Ã¥·¥ç¥ë¥É |
Abstract | ¾ÃÈñÅÅÎϤ¬¿ô¦ÌW°Ê²¼¤Î¥¹¥Þ¡¼¥È¥»¥ó¥µLSI¤ò¼Â¸½¤¹¤ë¤¿¤á¤Ë¡¢MOSFET¤ò¥µ¥Ö¥¹¥ì¥Ã¥·¥ç¥ë¥ÉÎΰè¤ÇÆ°ºî¤µ¤»¤Æ¶ËÄã¾ÃÈñÅÅÎϲ½¤ò¼Â¸½¤¹¤ë¤³¤È¤ò¹Í¤¨¤ë¡£¤³¤Î¾ì¹ç¤Ë¤Ï¡¢MOS²óÏ©¤ò¤«¤Ê¤êÄ㤤ÅÅ°µ¤ÇÆ°ºî¤µ¤»¤ë¤³¤È¤Ë¤Ê¤ë¡£¤½¤Î¤¿¤á¡¢³°ÉôÅŸ»¤ÎÅÅ°µ¤ò¸úΨ¤è¤¯ÄãÅÅ°µ¤Ë²¼¤²¤ëɬÍפ¬¤¢¤ë¡£Ëܸ¦µæ¤Ç¤Ï¡¢¥µ¥Ö¥¹¥ì¥Ã¥·¥ç¥ë¥ÉMOS LSI¤ËÄãÅÅÎϤò¶¡µë¤¹¤ë¤¿¤á¤Î¥¹¥¤¥Ã¥Á¥È¥¥ã¥Ñ¥·¥¿·¿DC-DC¹ß°µ¥³¥ó¥Ð¡¼¥¿¤Ë¤Ä¤¤¤Æ½Ò¤Ù¤ë¡£ |
Âê̾ | A Sub-1-V Low-Voltage Low-Power Reference With a Back-Gate Connection MOSFET |
Ãø¼Ô | ¡ûJun Pan, Yasuaki Inoue(Graduate School of Information, Production and Systems, Waseda University) |
Page | pp. 411 - 416 |
Keyword | reference, back-gate, low-voltage, low-power |
Abstract | A sub-1-V self-biased low-voltage low-power reference is presented for micropower electronic applications. The proposed circuit has very low temperature dependence by using a back-gate connection MOSFET. An Hspice simulation shows that the reference voltage and total power dissipation are 181 mV and 1.1 uW, respectively. The temperature coefficient of the reference voltage is 33 ppm/C within a temperature range from -40 to 100 C. The supply voltage dependence is -0.36 mV/V (Vdd=0.95~3.3 V), and the supply voltage can be as low as 0.95 V in a standard CMOS 0.35 um technology with threshold voltages of about 0.5 V and -0.65 V for n-channel and p-channel MOSFETs, respectively. |
Âê̾ | ¥ß¥¹¥Þ¥Ã¥Á¤Î±Æ¶Á¤òÄ㸺¤·¤¿¥ß¥Ã¥¯¥¹¥â¡¼¥É¥«¥¹¥±¡¼¥É·¿¦¤¦²DAC |
Ãø¼Ô | ¡ûÁ´ ¿¿À¸, ¼ÆÅÄ À¯ÈÏ, ¾ï¸« ÂîÌé, °ÂÅÄ ¾´(Ë¡À¯Âç³Ø) |
Page | pp. 417 - 422 |
Keyword | DAC |
Abstract | ËÜÏÀʸ¤Ç¤Ï¡¢¥ß¥¹¥Þ¥Ã¥Á¥·¥§¡¼¥Ô¥ó¥°µ¡Ç½¤ò´Þ¤á¤¿¥¢¥Ê¥í¥°FIR¥Õ¥£¥ë¥¿¤òÍѤ¤¤¿¥«¥¹¥±¡¼¥É·¿¦¤¦²DAC¤Î¹½À®Ë¡¤òÄó°Æ¤¹¤ë¡£¥ß¥¹¥Þ¥Ã¥Á¥·¥§¡¼¥Ô¥ó¥°µ¡Ç½¤Ï¾¯¿ô¤Î¥¹¥¤¥Ã¥Á¤À¤±¤Ë¤è¤Ã¤Æ¼Â¸½¤¹¤ë¤³¤È¤¬¤Ç¤¡¢¥ß¥¹¥Þ¥Ã¥Á¥·¥§¡¼¥Ô¥ó¥°µ¡Ç½¤Î¥Ï¡¼¥É¥¦¥§¥¢¥µ¥¤¥º¤òÂçÉý¤Ë¸º¾¯¤¹¤ë¤³¤È¤¬¤Ç¤¤ë¡£¤Þ¤¿¡¢¥¢¥Ê¥í¥°FIR¥Õ¥£¥ë¥¿¤òÍѤ¤¤ë¤³¤È¤Ç¡¢DAC¤Ë¸åÃÖ¤µ¤ì¤ë¥í¡¼¥Ñ¥¹¥Õ¥£¥ë¥¿¤Ø¤ÎÍ×µá¤ò´ËϤ¹¤ë¤³¤È¤¬²Äǽ¤È¤Ê¤ë¡£ |
Âê̾ | ¥Þ¥ë¥Á¥Ð¥ó¥É¥Ñ¥¹¦¤¦²ÊÑÄ´´ïÍÑDWA¥¢¥ë¥´¥ê¥º¥à¤È¤½¤Î±þÍÑ |
Ãø¼Ô | ¡û¸µß· ÆÆ»Ë , Ç븶 ¹Ç·, »³ÅÄ ²Â±û, ¾®ÎÓ ½ÕÉ×, ¾®¼¼ µ®µª, »± Úß(·²ÇÏÂç³Ø¹©³ØÉôÅŵ¤ÅŻҹ©³Ø²Ê/¾®ÎÓ¸¦µæ¼¼) |
Page | pp. 423 - 428 |
Keyword | ¦¤¦²ÊÑÄ´´ï, ¥Þ¥ë¥Á¥Ð¥ó¥É, ¥Þ¥ë¥Á¥Ó¥Ã¥È, DWA¥¢¥ë¥´¥ê¥º¥à, ¥Î¥¤¥º¥·¥§¡¼¥Ô¥ó¥° |
Abstract | ¤³¤ÎÏÀʸ¤Ç¤Ï¥Þ¥ë¥Á¥Ð¥ó¥É¥Ñ¥¹¦¤¦²ÊÑÄ´´ï¤ÎDWA(Data Weighted Averaging)¥¢¥ë¥´¥ê¥º¥à¤È¤½¤Î±þÍѤÎÄó°Æ¤ò¹Ô¤Ê¤¦. ¦¤¦²ÊÑÄ´´ï¤Î ÆâÉôADC/DAC¤Î¥Þ¥ë¥Á¥Ó¥Ã¥È²½¤Ëȼ¤¬DAC¤ÎÈóÀþ·ÁÀ¤¬ÌäÂê¤È ¤Ê¤ë¤¬¡¢¥Þ¥ë¥Á¥Ð¥ó¥É¥Ñ¥¹ÊÑÄ´´ï¤Î¾ì¹ç¤Ë ¤½¤Î±Æ¶Á¤òÍÞ¤¨¤ë¤¿¤á¤ÎDWA¥¢¥ë¥´¥ê¥º¥à¤òÄó°Æ¤¹¤ë. ¤Þ¤¿¤³¤ÎÄó°ÆDWA¥¢¥ë¥´¥ê¥º¥à¤Î¾¤ÎÍÍ¡¹¤ÊÊÑÄ´´ï¤Ø¤Î±þÍѤò¼¨¤·¡¢ ¤½¤Î͸úÀ¤ò,MATLAB¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤Ç³Îǧ¤·¤¿. |
Âê̾ | Verilog-A¤Ë¤è¤ë¥Ó¥Ø¥¤¥Ó¥¢¥â¥Ç¥ê¥ó¥°¤È¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤òÍøÍѤ·¤¿¦¤¦²ÊÑÄ´´ï¤Î¥³¥ó¥«¥ì¥ó¥ÈÀß·× |
Ãø¼Ô | ¡û»³ËÜ ¾Ïʸ(ÀŲ¬Âç³ØÂç³Ø±¡Íý¹©³Ø¸¦µæ²Ê), ÎëÌÚ ÊÙ(ÀŲ¬Âç³ØÅŻҲʳظ¦µæ²Ê), Àõ°æ ½¨¼ù(ÀŲ¬Âç³Ø¹©³ØÉô) |
Page | pp. 429 - 433 |
Keyword | Verilog-A, ¥Ó¥Ø¥¤¥Ó¥¢¥â¥Ç¥ë, ¦¤¦²ÊÑÄ´ |
Abstract | ËܹƤǤϡ¢¥¢¥Ê¥í¥°/¥Ç¥£¥¸¥¿¥ëº®ºÜ²óÏ©¤Î°ì¤Ä¤Ç¤¢¤ë¦¤¦²ÊÑÄ´´ï¤Î¥³¥ó¥«¥ì¥ó¥ÈÀß·×¼êË¡¤ò¼¨¤¹¡£Äó°Æ¼êË¡¤Ç¤Ï¡¢¥·¥¹¥Æ¥à¤ò¥Ó¥Ø¥¤¥Ó¥¢¥â¥Ç¥ë¤È¾ÜºÙ¤Ê¥â¥Ç¥ë¤Ë¤è¤ëº®ºÜ¥â¥Ç¥ë¤Çµ½Ò¤¹¤ë¡£°ìÎã¤È¤·¤Æ¡¢ÀÑʬ´ï¤È¤·¤Æ¥¹¥¤¥Ã¥Á¥È¥¥ã¥Ñ¥·¥¿¡ÊSC¡Ë¤òÍѤ¤¤ëÎ¥»¶»þ´Ö·¿¤Î°ì¼¡¦¤¦²ÊÑÄ´´ï¤ÎÀ߷פò¼¨¤¹¡£Àß·×¼ê½ç¤È¤·¤Æ¡¢µ¡Ç½¥Ö¥í¥Ã¥¯¤´¤È¤ËVerilog-A¤òÍѤ¤¤Æ¥Ó¥Ø¥¤¥Ó¥¢¥â¥Ç¥ë¤òºîÀ®¤¹¤ë¡£¼¡¤Ë¡¢ºîÀ®¤·¤¿¥Ó¥Ø¥¤¥Ó¥¢¥â¥Ç¥ë¤òÍѤ¤¤Æ¥ª¥Ú¥¢¥ó¥×¤Î»ÅÍͤò·èÄꤹ¤ë¡£ºÇ¸å¤Ë³Æµ¡Ç½¥Ö¥í¥Ã¥¯¤ò¥È¥é¥ó¥¸¥¹¥¿¥ì¥Ù¥ë¤ÇÀ߷פ·¡¢µ¡Ç½¥Ö¥í¥Ã¥¯¤´¤È¤Ë¥Ó¥Ø¥¤¥Ó¥¢¥â¥Ç¥ë¤ò²óÏ©¤ÈÃÖ¤´¹¤¨¤Æ¤¤¤¯¤³¤È¤Ë¤è¤ê°ì¼¡¦¤¦²ÊÑÄ´´ï¤ÎÀ߷פò¹Ô¤¦¡£ |
Âê̾ | ÄãÅÅ°µCMOS¥³¥ó¥Ñ¥ó¥Ç¥£¥ó¥°¥í¥°¥É¥á¥¤¥óÀÑʬ²óÏ©¤ÎÁ´Ãµº÷¤Ë¤è¤ëºÇŬÀß·×Ë¡ |
Ãø¼Ô | ¡û½©ÅÄ °ìÊ¿(˶¶µ»½Ñ²Ê³ØÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²ÊÇî»Î¸å´ü²ÝÄø ÅŻҡ¦¾ðÊ󹩳ØÀ칶), ÏÂÅÄ ÏÂÀé, ÅÄ½ê ²Å¾¼(˶¶µ»½Ñ²Ê³ØÂç³Ø¹©³ØÉô¾ðÊ󹩳زÝÄø) |
Page | pp. 435 - 440 |
Keyword | ÄãÅÅ°µ, ÀÑʬ²óÏ©, ¥¢¥Ê¥í¥°¥Õ¥£¥ë¥¿, ¥³¥ó¥Ñ¥ó¥Ç¥£¥ó¥°, ¥í¥°¥É¥á¥¤¥ó |
Abstract | ÄãÅÅ°µ¤«¤Ä¹¥À¥¤¥Ê¥ß¥Ã¥¯¥ì¥ó¥¸¤Ê¥¢¥Ê¥í¥°¿®¹æ½èÍý¤ò¼Â¸½¤¹¤ë°ì¼êË¡¤È¤·¤Æ¡¤¥³¥ó¥Ñ¥ó¥Ç¥£¥ó¥°²óÏ©µ»½Ñ¤¬¤¢¤ë¡¥ËÜÏÀʸ¤Ç¤Ï¡¤½¾Íè¸ÄÊ̤˹ͤ¨¤é¤ì¤Æ¤¤¿ÄãÅÅ°µCMOS¥³¥ó¥Ñ¥ó¥Ç¥£¥ó¥°ÀÑʬ²óÏ©¤òÅý°ìŪ¤Ë¼è¤ê°·¤¦¤³¤È¤Ç¡¤ºÇŬÀ߷פμêË¡¤òÄó°Æ¤¹¤ë¡¥¥³¥ó¥Ñ¥ó¥Ç¥£¥ó¥°ÀÑʬ²óÏ©¤Î¸¶Íý¤ÇɬÍפȤʤ뤤¤¯¤Ä¤«¤ÎÉôʬ²óÏ©¤Î¼Â¸½¤Ë¼«Í³ÅÙ¤¬¤¢¤ë¤³¤È¤ò»ØŦ¤·¡¤¤½¤ì¤é¤ÎÁȹç¤ï¤»¤Ç¿¤¯¤ÎÀÑʬ²óÏ©¤ò¹½À®¤¹¤ë¡¥ËÜÀ߷פˤè¤ê¡¤Á´¤Æ¤Î¥³¥ó¥Ñ¥ó¥Ç¥£¥ó¥°ÀÑʬ²óÏ©¤Î¹½À®¤òÎóµó¤Ç¤¡¤ºÇŬ¤Ê²óÏ©¹½À®¤¬Ãµº÷²Äǽ¤È¤Ê¤ë¡¥ |
Âê̾ | A Highly Linear and Wide Dynamic Range Four-quadrant CMOS Analog Multiplier Using Active Feedback |
Ãø¼Ô | ¡ûZhangcai Huang, Yasuaki Inoue, Quan Zhang, Hong Yu(Waseda University) |
Page | pp. 441 - 445 |
Keyword | CMOS Analog Multiplier, Active Feedback |
Abstract | A new circuit configuration for an CMOS fourquadrant analog multiplier is presented. In this circuit, the active feedback technique is used to obtain high linearity and wide input dynamic range. The experimental results show that the proposed multiplier can offer +-1.8V input dynamic range for a +-2.5V supply voltage, which are much larger than the previous CMOS analog multiplier. |
Âê̾ | ¥é¥Æ¥£¥é¥ëÅý¹çC-BiCMOS¥Ð¥Ã¥Õ¥¡¶îÆ°¤ÎCMOS¥¯¥í¥Ã¥¯À¸À®²óÏ© |
Ãø¼Ô | ¡ûßÀȪ ¹§(¶áµ¦Âç³ØÂç³Ø±¡À¸ÊªÍý¹©³Ø¸¦µæ²Ê), ½©Ç» ½ÓϺ(¶áµ¦Âç³Ø) |
Page | pp. 447 - 452 |
Keyword | SOI, Éôʬ¶õ˳ÁØ, C-BiCMOS, ¥é¥Æ¥£¥é¥ëBJT |
Abstract | SOI´ðÈľå¤ÎÉôʬ¶õ˳·¿CMOS¥¤¥ó¥Ð¡¼¥¿¤Ç¡¢MOSFET¤ÈBJT¤ÎÊÂÎóº®À® ¥â¡¼¥ÉÆ°ºî¤¬Äó°Æ¤µ¤ì¡¢¤½¤Î²óÏ©À߷פȲóÏ©¥·¥ß¥å¥ì¡¼¥¿¤Ë¤è¤ë ¸¡¾Ú¤¬¹Ô¤ï¤ì¤ÆÍ褿¡£¤³¤Î¥¤¥ó¥Ð¡¼¥¿¤ò¹½À®¤¹¤ë4ü»Ò¤În{p}¥Á¥ã ¥Í¥ëMOSFET¤Ï¡¢3ü»Ò¤Î¥é¥Æ¥£¥é¥ënpn{pnp}BJT¤òÆ⸤¹¤ë¡£Ä̾ï¤Î ¶¦Í¤·¤¿´ðÈĤΥץ륢¥Ã¥×¡¿¥×¥ë¥À¥¦¥óMOSFET¤òÅÅή¸»¤È¤·¤Æ¡¢ ¤½¤Î¥É¥ì¥¤¥óü»Ò¤«¤é¥é¥Æ¥£¥é¥ë¡¦¥Ç¥Ð¥¤¥¹¤òÅý¹ç(Unified) C-BiCMOS¤È¸Æ¤Ö¡Ú°Ê¹ßUC-BiCMOS¤Èµ¤¹¡Û¡£½¾Íè¤ÎUC-BiCMOS¤Î ¸¦µæ¤Ç¤Ï¡¢CMOS¥¤¥ó¥Ð¡¼¥¿¤Î¥²¡¼¥Èü»Ò¤È¡¢Æ⸤¹¤ëBJT¤ò ³èÀ²½¤¹¤ë¥×¥ë¥¢¥Ã¥×¡¿¥×¥ë¥À¥¦¥óMOSFET¤Î¥²¡¼¥Èü»Ò¤ÎξÊý¤ò ÆþÎϤȤ·¤¿¤¬¡¢Ëܸ¦µæ¤Ç¤Ï¥×¥ë¥¢¥Ã¥×¡¿¥×¥ë¥À¥¦¥óMOSFET¤Î¥²¡¼¥È ü»Ò¤Î¤ß¤òÆþÎϤȤ¹¤ë²óÏ©Êý¼°¤òÄó°Æ¤¹¤ë¡£Â¨¤Á¡¢º®À®¥â¡¼¥É¤Î ξMOSFET¤Ï¡Ö¥ª¥Õ¡×¤Î¾õÂ֤˸ÇÄꤷ¤Æ¡¢Î¾¥é¥Æ¥£¥é¥ëBJT¤Î¤ß¤¬ ¶îÆ°¤¹¤ë¥Ð¥Ã¥Õ¥¡²óÏ©¤È¤Ê¤ë¡£¹¹¤Ë¡¢¥ê¥ó¥°¥ª¥·¥ì¡¼¥¿¤Îȯ¿¶ ÇÈ·Á¤ò¶îÆ°¤¹¤ë¥Ð¥Ã¥Õ¥¡²óÏ©¤È¤·¤Æ±þÍѤ¹¤ë¡£¤³¤³¤Ç¤Ï0.35¦Ìm¤Î CMOS¥×¥í¥»¥¹¤ËÂФ¹¤ë²óÏ©¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤ò¹Ô¤Ã¤Æ¡¢¤½¤ì¤é¤Î ²óÏ©ÆÃÀ¤òÄ´¤Ù¤ë¡£Éé²ÙÍÆÎÌCout=1.417pF¤ÇÅŸ»ÅÅ°µVdd=1V¤Î ¾ì¹ç¡¢21ÃÊ¥¤¥ó¥Ð¡¼¥¿¤Î¥ê¥ó¥°¥ª¥·¥ì¡¼¥¿¤ÎÇÈ·Á¤òUC-BiCMOS ¥Ð¥Ã¥Õ¥¡¤ËÆþÎϤ¹¤ë¾ì¹ç¤Ï¡¢¥Õ¥¡¥ó¥¢¥¦¥È4¤Î4ÃÊCMOS¥¤¥ó¥Ð¡¼¥¿ ¤Î¾ì¹ç¤ËÈæ¤Ù¤Æ¡¢4Çܰʾå¹â®¤Ç¡¢Ìó36%¥¨¥Í¥ë¥®¡¼¤¬Ä㤤¡£ |
Âê̾ | ¥¹¥±¡¼¥ê¥ó¥°¤ò¹Íθ¤·¤¿½ä²ó·¿¥Ç¥£¥¸¥¿¥ë¥Õ¥£¥ë¥¿¤Î͸¸ìĹÀß·×Ë¡ |
Ãø¼Ô | ¡ûÃæËÜ ¾»Í³, ¿÷¸µ ¹§É×, ±ü Àµ´ð, µÈ²° ¹ä(¹ÅçÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²Ê) |
Page | pp. 453 - 458 |
Keyword | ½ä²ó·¿¥Ç¥£¥¸¥¿¥ë¥Õ¥£¥ë¥¿, ¥¹¥±¡¼¥ê¥ó¥°, ͸¸ìĹÀß·×, ʬ»Þ¸ÂÄêË¡, ºÇŬ²½ |
Abstract | ËÜÏÀʸ¤Ç¤Ï¡¤¥¹¥±¡¼¥ê¥ó¥°À©Ì󲼤ˤª¤±¤ëÎ¥»¶¥Õ¥£¥ë¥¿·¸¿ô¤ÎÀß·×Ë¡¤òÄó°Æ¤¹¤ë¡¥¤³¤³¤Ç¤Ï¡¤Lu¤é¤Ë¤è¤Ã¤ÆÄó°Æ¤µ¤ì¤¿·«¤êÊÖ¤·ºÇŬ²½Ë¡¤Ë¤è¤Ã¤Æ2¼¡·Á¼°¤Î¹ÔÎó¤È¥Ù¥¯¥È¥ë¤òµá¤á¤Æ¤ª¤¡¤¼¡¤¤¤Çõº÷ÈϰϤò¸ÂÄꤹ¤ë¤¿¤á¤ËLagrange¤Î̤Äê¾è¿ôË¡¤òÍѤ¤¤Æ²¼²òÃͤòɾ²Á¤·¤Ä¤ÄÎ¥»¶ºÇŬ²½¤ò¹Ô¤¦¡¥¼¡¤Ë¥¹¥±¡¼¥ê¥ó¥°·¸¿ô¤òÎ¥»¶Ãͤǵá¤á¤Æ¤ª¤¡¤Àß·×»ÅÍÍ¡ÊÍýÁÛ¼þÇÈ¿ô±þÅú¡Ë¤Ë¤½¤ÎµÕ¿ô¤ò¾è¤¸¤Æ½¤Àµ¤¹¤ë¤³¤È¤Ë¤è¤Ã¤Æ¡¤ºÆÅÙ¥Õ¥£¥ë¥¿·¸¿ô¤òÀ߷פ¹¤ë¡¥Àß·×Îã¤Ç¤Ï¡¤Äã°èÄ̲ᡦ¹â°èÄ̲á¥Õ¥£¥ë¥¿¤òÀ߷פ·¡¤Äó°Æ¼êË¡¤Î͸úÀ¤ò¼¨¤¹¡¥ |
Âê̾ | 2¼¡¾õÂÖ¶õ´Ö¥Ç¥£¥¸¥¿¥ë¥Õ¥£¥ë¥¿¤Î¥¹¥±¡¼¥ê¥ó¥°¤ò¹Íθ¤·¤¿L2´¶ÅٺǾ®²½ÌäÂê¤ÎÊĤ¸¤¿·Á¤Î²òË¡ |
Ãø¼Ô | ¡ûȬ´¬ ½ÓÊå, °¤Éô Àµ±Ñ, ÀîËô À¯À¬(ÅìËÌÂç³ØÂç³Ø±¡¹©³Ø¸¦µæ²ÊÅŻҹ©³ØÀ칶) |
Page | pp. 459 - 464 |
Keyword | ¾õÂÖ¶õ´Ö¥Ç¥£¥¸¥¿¥ë¥Õ¥£¥ë¥¿, L2´¶ÅÙ, L2¥¹¥±¡¼¥ê¥ó¥°À©Ìó, ÊĤ¸¤¿·Á¤Î²òË¡ |
Abstract | ËÜÏÀʸ¤Ç¤Ï¡¢2¼¡¤Î¥Ç¥£¥¸¥¿¥ë¥Õ¥£¥ë¥¿¤òÂоݤȤ·¤Æ¡¢¥¹¥±¡¼¥ê¥ó¥°¤ò¹Íθ¤·¤¿L2´¶ÅٺǾ®²½ÌäÂê¤ÎÊĤ¸¤¿·Á¤Î²òË¡¤ÎƳ½Ð¤òÌÜŪ¤È¤¹ ¤ë¡£¤³¤ÎÌäÂê¤Ï¡¢L2´¶ÅٺǾ®²½ÌäÂê¤ËÆâÉô¾õÂ֤Υª¡¼¥Ð¡¼¥Õ¥í¡¼¤òÍÞÀ©¤¹¤ëÀ©Ìó¾ò·ï¤òÁȤ߹þ¤ó¤À¤â¤Î¤Ç¤¢¤ë¡£¤Þ¤º¡¢½é´ü¾ò·ï¤òŬÀÚ¤ËÁª¤Ö¤³¤È¤Ë¤è¤Ã¤Æ¡¢À©Ìó¾ò·ï¤ò´Êñ²½¤¹¤ë¡£¼¡¤Ë¡¢ÊÑ´¹¹ÔÎó¤ËÂФ·¤ÆŬÀÚ¤ÊÊÑ¿ôÊÑ´¹¤ò»Ü¤¹¤³¤È¤Ë¤è¤ê¡¢À©Ìó¾ò·ï¤Ä¤¤ÎºÇŬ²½ÌäÂê¤òÀ©Ìó¾ò·ï¤Ê¤·¤ÎºÇŬ²½ÌäÂê¤Ëµ¢Ã夵¤»¤ë¡£¤½¤·¤Æ¡¢2¼¡¤Î¥Õ¥£¥ë¥¿¤òÂоݤȤ¹¤ë¤³¤È¤Ç¡¢L2´¶ÅÙ¤òÊĤ¸¤¿·Á¤Çɽ¤¹¡£¤½¤Î·ë²Ì¡¢¥¹¥±¡¼¥ê¥ó¥°¤ò¹Íθ¤·¤¿L2´¶ÅٺǾ®²½ÌäÂê¤ËÂФ·¤Æ¡¤Ã༡Ū·×»»¤ò»È¤ï¤Ê¤¤ÊĤ¸¤¿·Á¤Î²òË¡¤¬Æ³½Ð¤µ¤ì¤ë¡£ |
Âê̾ | The Optimum Approximation of a FIR Filter Bank Realizing Simultaneous Minimization of Various Worst-Case Measures of Error |
Ãø¼Ô | ¡ûYuichi Kida(School of Pharmaceutical Sciences, Ohu University), Takuro Kida(Department of EE Eng., Nihon University) |
Page | pp. 465 - 470 |
Keyword | digital signal processing, interpolation approximation, filter bank |
Abstract | We present the optimum approximation of FIR filter bank that minimizes various measures of error of approximation, simultaneously. The presented approximation is quite flexible in choosing band-width of sub-bands, sample points and analysis filters. |
Âê̾ | ¦¤¦²ÊÑÄ´¤È¥ª¡¼¥Ð¡¼¥µ¥ó¥×¥ê¥ó¥°¤òÍѤ¤¤¿°ÌÃÖÆâÁޤΤ¿¤á¤Î¥Ç¥£¥¸¥¿¥ë°ÌÁêÄɽ¾¥ë¡¼¥×¤Î¸¡Æ¤ |
Ãø¼Ô | ¡ûÀÞÌî ͵°ìϺ, ¹õß· ¼Â(Åìµþ¹©¶ÈÂç³Ø Áí¹çÍý¹©³Ø¸¦µæ²Ê), ÊÒ¶Í ¿ò(¤¹¤Æ¤¤Ê(Í)) |
Page | pp. 471 - 476 |
Keyword | ¦¤¦²ÊÑÄ´, ¥ª¡¼¥Ð¡¼¥µ¥ó¥×¥ê¥ó¥°, ÆâÁÞ, ¥»¥ó¥µ¿®¹æ½èÍý |
Abstract | ¥ì¥¾¥ë¥Ð¤ä¥¤¥ó¥¯¥ê¥á¥ó¥¿¥ë¥¨¥ó¥³¡¼¥ÀÅù¤Î¥»¥ó¥µ¤Ç¤Ï¤è¤ê¹âÀºÅ٤ʰÌÃÖ¸¡½Ð¤Î¤¿¤á¤ËÆâÁޤȤ¤¤¦¿®¹æ½èÍý¤¬É¬ÍפȤµ¤ì¤ë¡£ÆâÁÞ¤ò¼Â¸½¤¹¤ë¤¿¤á¤ÎÊýË¡¤Î¤¦¤Á¡¢2Áê(Ê£ÁÇ)°ÌÁêƱ´ü¥ë¡¼¥×¤Î¸¶Íý¤Ë´ð¤Å¤¯¥¢¥ë¥´¥ê¥º¥à¤Ë¤Ä¤¤¤Æ¡¢²óÏ©µ¬ÌϤòÍÞ¤¨¤ë¤³¤È¤òÌÜŪ¤È¤·¤¿¿·¤¿¤Ê¥·¥¹¥Æ¥à¹½À®¤ò¸¡Æ¤¤·¤¿¡£Äó°Æ¼êË¡¤Ï¦¤¦²ÊÑÄ´¤È¥ª¡¼¥Ð¡¼¥µ¥ó¥×¥ê¥ó¥°¤Ë¤è¤ë¿®¹æ½èÍý¥¢¡¼¥¥Æ¥¯¥Á¥ã¤Ë´ð¤Å¤¤¤Æ¤¤¤ë¡£ËÜÏÀʸ¤Ç¤Ï´Êñ¤Ê¥·¥¹¥Æ¥à¹½À®¤òÎ㼨¤·¡¢¤½¤Î¥·¥¹¥Æ¥à¤ÎÀǽ¤ò¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤Ç¸¡Æ¤¤·¤¿·ë²Ì¤ò¼¨¤¹¡£ |
Âê̾ | Ŭ±þ¥Õ¥£¥ë¥¿¤Ë¤ª¤±¤ë¦¤¦²ÊÑÄ´¤Ë´ð¤Å¤¯1¥Ó¥Ã¥È¿®¹æ½èÍý¤Î±é»»ÀºÅÙ¤Îɾ²Á |
Ãø¼Ô | ¡û°ËÆ£ ͪÆó, ¼¶¶ Á±¸÷, Æ»ÌÚ ¿µÆó, Âç·§ ÈË(̾¸Å²°Âç³ØÂç³Ø±¡) |
Page | pp. 477 - 481 |
Keyword | ¦¤¦²ÊÑÄ´, 1¥Ó¥Ã¥È¿®¹æ½èÍý, Ŭ±þ¥Õ¥£¥ë¥¿ |
Abstract | É®¼Ô¤é¤Ï¡¢¦¤¦²ÊÑÄ´¤Ë´ð¤Å¤¯1¥Ó¥Ã¥È¿®¹æ½èÍý¤òÍѤ¤¤Æ¿ô¼ïÎà¤Î¥Ë¥å¡¼¥é¥ë¥Í¥Ã¥È¥ï¡¼¥¯(NN)¤ò¼Â¸½¤·¤Æ¤¤¿¡£¤½¤Î¸¦µæÀ®²Ì¤Ë¤ª¤¤¤Æ¡¢¥ª¡¼¥Ð¡¼¥µ¥ó¥×¥ê¥ó¥°¤ò1024ÇܤȤ·¤ÆºîÀ®¤·¤¿1¥Ó¥Ã¥ÈNN¤È¡¢¤½¤ì¤ËÁêÅö¤¹¤ë11¥Ó¥Ã¥È¤Î¸ÇÄê¾®¿ôÅÀNN¤òÈæ³Ó¤·¤¿¤È¤³¤í¡¢Á°¼Ô¤ÏÁÛÄê°Ê¾å¤Î±é»»ÀºÅÙ¤òͤ¹¤ë¤³¤È¤¬¼¨¤µ¤ì¤¿¡£¤½¤³¤Ç¡¢¤³¤Î¥Ñ¥é¥á¡¼¥¿¹¹¿·±é»»¤Ë¤ª¤±¤ë1¥Ó¥Ã¥È¿®¹æ½èÍý¤ÎÀ¼Á¤òÌÀ¤é¤«¤Ë¤¹¤ë¤¿¤á¡¢¤è¤ê¥·¥ó¥×¥ë¤Ê1¥Ñ¥é¥á¡¼¥¿¤ÎŬ±þ¥Õ¥£¥ë¥¿¤Ë¤ª¤±¤ë¦¤¦²ÊÑÄ´¤Ë´ð¤Å¤¯1¥Ó¥Ã¥È¿®¹æ½èÍý¤Î±é»»ÀºÅÙ¤Îɾ²Á¤ò¹Ô¤¦¡£¤½¤·¤ÆËܹƤǤϡ¢¥Þ¥ë¥Á¥Ó¥Ã¥È¸ÇÄê¾®¿ôÅÀ±é»»¤È1¥Ó¥Ã¥È±é»»¤Î¥Ñ¥é¥á¡¼¥¿¼ý«ÃͤÎÀºÅÙ¤ÎÈæ³Ó¤ò¹Ô¤¤¡¢¤½¤Î¥·¥ß¥å¥ì¡¼¥·¥ç¥ó·ë²Ì¤ò¼¨¤¹¡£ |
Âê̾ | µ÷Î¥·×¬¤Ë¤è¤ë¥Ï¥¦¥ê¥ó¥°½üµî |
Ãø¼Ô | ¡ûÀî¼ ¿·, Æ£ËÜ ¸î, ÈÓÔ¢ ÍÎÆó(ÂçºåÂç³Ø) |
Page | pp. 483 - 488 |
Keyword | ¥Ï¥¦¥ê¥ó¥°¥¥ã¥ó¥»¥é, µ÷Î¥·×¬, ¥Î¥Ã¥Á¥Õ¥£¥ë¥¿ |
Abstract | ËÜÏÀʸ¤Ç¤Ï¡¤¥¹¥Ô¡¼¥«¡Ý¥Þ¥¤¥¯¥í¥Û¥ó´Ö¤Îµ÷Î¥¤«¤é¥Ï¥¦¥ê¥ó¥°¼þÇÈ¿ô¤òµá¤á¡¤¤½¤Î¼þÇÈ¿ô¤ò½üµî¤¹¤ë¡¤¥Ï¥¦¥ê¥ó¥°½üµî¥·¥¹¥Æ¥à¤òÄó°Æ¤¹¤ë¡¥Äó°ÆË¡¤Ç¤Ï¡¤¤Þ¤º¡¤¥¹¥Ô¡¼¥«¡Ý¥Þ¥¤¥¯¥í¥Û¥ó´Ö¤Îµ÷Î¥¤ò²»ÇȤˤè¤ê·×¬¤·¡¤¼¡¤Ë¡¤·×¬¤µ¤ì¤¿µ÷Î¥¤«¤é¥Ï¥¦¥ê¥ó¥°¤È¤Ê¤ë¼þÇÈ¿ô¤Î¸õÊä¤ò¿äÄꤹ¤ë¡¥¤½¤·¤Æ¡¤¿äÄꤵ¤ì¤¿¼þÇÈ¿ôÀ®Ê¬¤ò¥Î¥Ã¥Á¥Õ¥£¥ë¥¿¤Ë¤è¤ê½üµî¤¹¤ë¡¥Äó°ÆË¡¤Ë¤è¤ì¤Ð¡¤¥Ï¥¦¥ê¥ó¥°¤ò¤¢¤é¤«¤¸¤á½üµî¤·¤Æ¤ª¤¯¤¿¤á¡¤¥Ï¥¦¥ê¥ó¥°¤½¤Î¤â¤Î¤¬À¸¤¸¤Ê¤¤¤È¤¤¤¦ÆÃħ¤¬¤¢¤ë¡¥¤Þ¤¿¡¤Ã»»þ´Ö¤Ç·×¬µ÷Î¥¤ò¹¹¿·¤¹¤ë¤³¤È¤¬²Äǽ¤Ç¤¢¤ë¤¿¤á¡¤¥Þ¥¤¥¯¥í¥Û¥ó¤¬°ÜÆ°¤·¤¿¾ì¹ç¤Ë¤âÂбþ¤Ç¤¤ë¡¥Æäˡ¤Äó°ÆË¡¤Ç¤Ï¡¤½¾Íè¤Î¥Ï¥¦¥ê¥ó¥°¥¥ã¥ó¥»¥é¤Ç½ÅÍפȤʤ롤¥Õ¥£¥ë¥¿·¸¿ô¤Î¼ý«®ÅÙ¤ò¹Í¤¨¤ëɬÍפ¬¤Ê¤¤¤È¤¤¤¦ÆÃŤ¬¤¢¤ë¡¥ºÇ¸å¤Ë¡¤DSP¾å¤Ë¥Ï¥¦¥ê¥ó¥°½üµî¥·¥¹¥Æ¥à¤ò¼Â¸½¤·¡¤¼Â´Ä¶¤Ë¤ª¤±¤ëÄó°ÆË¡¤Î͸úÀ¤ò³Îǧ¤¹¤ë¡¥ |
Âê̾ | ¥¹¥Ñ¡¼¥¹¿®¹æɽ¸½¤Ë¤è¤ë²»À¼¤«¤é¤ÎÆÍȯÀ»¨²»½üµî |
Ãø¼Ô | ¡ûÃæÀÅ ¿¿, ²¼Â¼ ľÌé, ÈÓÔ¢ ÍÎÆó(ÂçºåÂç³ØÂç³Ø±¡´ðÁù©³Ø¸¦µæ²Ê) |
Page | pp. 489 - 494 |
Keyword | ²»À¼¿®¹æ½èÍý, ÆÍȯÀ»¨²», Basis Pursuit, Basis Pursuit»¨²»½üµî, ¿®¹æʬΥ |
Abstract | ËÜÊó¹ð¤Ç¤Ï¡¤Basis Pursuit¤ò²»À¼¿®¹æ¤ÎÆÍȯÀ»¨²»½üµî¤ØŬÍѤ·¤Æ¤¤¤ë¡¥ÆÍȯÀ»¨²»¤Ï¡¤¤½¤ÎȯÀ¸»þ¹ï¤¬ÉÔµ¬Â§¤«¤Ä»ý³»þ´Ö¤¬Ã»¤¤¤³¤È¤«¤é¡¤»¨²»¥¹¥Ú¥¯¥È¥ë¤ª¤è¤ÓȯÀ¸»þ¹ï¤Î¿äÄ꤬º¤Æñ¤Ç¤ê¡¤¥¹¥Ú¥¯¥È¥ë¸º»»Ë¡Åù¤òŬÍѤ¹¤ë¤³¤È¤¬º¤Æñ¤Ê»¨²»¤Ç¤¢¤ë¡¥ËÜÊó¹ð¤Ç¤Ï¡¤²»À¼¿®¹æ¤ÈÆÍȯÀ»¨²»¤Î»ý³»þ´Ö¤Î°ã¤¤¤ËÃåÌܤ·¡¤Basis Puruit¤òÍѤ¤¤Æ°Û¤Ê¤ë2¤Ä¤Î¥Õ¥ì¡¼¥àŤÎDFT´ðÄ줽¤ì¤¾¤ì¤Ø»¨²»¤È²»À¼¿®¹æ¤òʬΥ¤¹¤ë¤³¤È¤òÄó°Æ¤·¤Æ¤¤¤ë¡¥ËÜÊó¹ð¤Ç¤ÏBlock Coordinate RelaxationË¡¤Ë¤è¤ëBasis Pursuit»¨²»½üµîË¡¤Ë¤è¤ê¶á»÷Ū¤ËÊ£ÁÇ´ðÄì·²¤Ë¤è¤ëBasis Pursuit¤ò¼Â¸½¤·¤Æ¤¤¤ë¡¥¼Â¸³¤Ç¤Ï¡¤·×»»µ¡¾å¤ÇºîÀ®¤·¤¿»¨²»¡¤¤ª¤è¤Ó»Ä¶Á¤Î¤¢¤ë¼Â´Ä¶¤ÇÏ¿²»¤µ¤ì¤¿»¨²»¤òÍѤ¤¤Æ»¨²»½üµî¼Â¸³¤ò¹Ô¤¤¡¤Í¸úÀ¤ò³Îǧ¤·¤Æ¤¤¤ë¡¥ |
Âê̾ | ¥â¥ë¥Õ¥©¥í¥¸¡¼¤òÍѤ¤¤¿²èÁü¤Î²þ¤¶¤ó¸¡½ÐË¡ |
Ãø¼Ô | ¡ûËü º¢Åó(¼óÅÔÂç³ØÅìµþÂç³Ø±¡), Æ£µÈ ÀµÌÀ, µ®²È ¿Î»Ö(¼óÅÔÂç³ØÅìµþ) |
Page | pp. 495 - 500 |
Keyword | ²þ¤¶¤ó, ¥â¥ë¥Õ¥©¥í¥¸¡¼, ¤Ù¤ÅùÀ, °µ½Ì, ¿ÃͲèÁü |
Abstract | ËܹƤϡ¤¥â¥ë¥Õ¥©¥í¥¸¡¼¤òÍѤ¤¤¿²èÁü¤Î²þ¤¶¤ó¸¡½ÐË¡¤òÄó°Æ¤·¤Æ¤¤¤ë¡¥Äó°ÆË¡¤Ï¡¤¥ª¡¼¥×¥Ë¥ó¥°½èÍý¤Î¤Ù¤ÅùÀ¤ËÃåÌܤ·¡¤ÅÅ»ÒÆ©¤«¤·¤òÍѤ¤¤º¤Ë²þ¤¶¤ó¡¤¤ª¤è¤Ó¡¤¤½¤Î°ÌÃ֤θ¡½Ð¤¬²Äǽ¤È¤Ê¤Ã¤Æ¤¤¤ë¡¥¤Þ¤¿¡¤JPEG¤Ê¤É¤ÎÈó²ÄµÕ°µ½ÌÂÑÀ¤âͤ·¤Æ¤¤¤ë¡¥Äó°ÆË¡¤Ë¤Ï3¤Ä¤Î¼«Í³ÅÙ¤¬¤¢¤ê¡¤¤³¤ì¤é¤ò³èÍѤ¹¤ë¤³¤È¤Ç¡¤¸¡½ÐǽÎϤ䰵½ÌÂÑÀ¤Ê¤É¤òÀ©¸æ²Äǽ¤È¤Ê¤Ã¤Æ¤¤¤ë¡¥¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤Ë¤è¤ê¡¤Äó°ÆË¡¤Î͸úÀ¤¬³Îǧ¤µ¤ì¤Æ¤¤¤ë¡¥ |
Âê̾ | ¶õ´ÖÎΰè¤Î²ÄµÕ¾ðÊóËä¹þ¤ß |
Ãø¼Ô | ¡û¶â ¹°ÎÓ(¼óÅÔÂç³ØÅìµþÂç³Ø±¡), Æ£µÈ ÀµÌÀ, µ®²È ¿Î»Ö(¼óÅÔÂç³ØÅìµþ) |
Page | pp. 501 - 506 |
Keyword | ²ÄµÕ·¿, È󻲾ȷ¿, Î̻Ҳ½·¿, ͸¸ìĹ, Æ©¤«¤· |
Abstract | ËܹƤǤϡ¤¶õ´ÖÎΰè¤Ë¤ª¤¤¤Æ²èÁÇÃͤؾðÊó¤òËä¤á¤ëÈ󻲾ȷ¿¾ðÊóËä¹þË¡¤òÄó°Æ¤¹¤ë¡¥Äó°ÆË¡¤Ï¡¢¾ðÊó¤¬Ëä¤á¤é¤ì¤¿²èÁü¤«¤é¾ðÊó¤òÃê½Ð¤Ç¤¤ë¤À¤±¤Ç¤Ê¤¯¡¤¸¶²èÁü¤âÉü¸µ²Äǽ¤Ê²ÄµÕ·¿¾ðÊóËä¹þ¤ßË¡¤Ç¤¢¤ë¡¥¾ðÊóËä¹þÂоݲèÁǤȤ½¤Î¼þÊÕ²èÁǤȤδʰפÊÅý·×Î̤òÍѤ¤¤ë¤³¤È¤Ç¡¤¥Ñ¥é¥á¥¿1¤Ä¤Î¤ß¤Ç¡¤¾ðÊó¤ÎÃê½Ð¤ª¤è¤Ó¸¶²èÁü¤ÎÉü¸µ¤¬²Äǽ¤È¤Ê¤Ã¤Æ¤¤¤ë¡¥¾ðÊó¤òËä¤á¤¿²èÁǤΰÌÃ֤ξðÊó¤âÉÔÍפǤ¢¤ë¡¥¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤Ë¤è¤ê¡¢Ëä¹þ²ÄǽºÇÂç¾ðÊóÎ̤¬É¾²Á¤µ¤ì¤Æ¤¤¤ë¡¥ |
Âê̾ | ưŪ¥Í¥Ã¥È¥â¥Ç¥ë¤Ë¤ª¤±¤ëÊáªǽÎϤβþÁ±¤Ë´Ø¤¹¤ë¸¡Æ¤ |
Ãø¼Ô | ¸ÅÎÓ Í¤²ð(ÄÅ»³¹©¶È¹âÅùÀìÌç³Ø¹»À칶²Ê), ¡ûÌùÌÚ ÅÐ(ÄÅ»³¹©¶È¹âÅùÀìÌç³Ø¹»¾ðÊ󹩳زÊ), Ïɸ« °éμ, ¾¾Á° ¿Ê, Ê¡ËÜ Á±ÍÎ(Ä»¼è´Ä¶Âç³Ø¾ðÊó³ØÉô¾ðÊó¥·¥¹¥Æ¥à³Ø²Ê), Éû°æ ͵(Ä»¼èÂç³Ø¹©³ØÉôÅŵ¤ÅŻҹ©³Ø²Ê) |
Page | pp. 507 - 512 |
Keyword | ưŪ¥Í¥Ã¥È¥â¥Ç¥ë, ¥¢¥¯¥Æ¥£¥Ö¥Í¥Ã¥È, ²èÁü, Îΰ踡½Ð |
Abstract | ËܹƤϡ¢Æ°Åª¥Í¥Ã¥È¥â¥Ç¥ë¤ÎÊáªÀǽ¤ÎÌäÂê¤È¤·¤Æ¡¢ÆþÎϲèÁü¤Ë¸ºß¤¹¤ë»¨²»¤Î±Æ¶Á¤Ë¤Ä¤¤¤Æ¸¡Æ¤¤ò¹Ô¤Ê¤Ã¤¿·ë²Ì¤Ë¤Ä¤¤¤Æ½Ò¤Ù¤Æ¤¤¤ë¡£ ½¾Íè¼êË¡¤Ë¤ª¤¤¤Æ¤Ï¡¢ÆþÎϲèÁü¤Ë¡¢¥¿¡¼¥²¥Ã¥È¤Î¾¤Ë»¨²»¤¬Â¸ºß¤·¤Æ¤·¤Þ¤Ã¤¿¾ì¹ç¡¢¥¿¡¼¥²¥Ã¥È¤È»¨²»¤ÎξÊý¤òÊ᪤·¡¢¥¿¡¼¥²¥Ã¥È¤Î¤ß¤ò¤½¤Î¤Þ¤Þ¤Ç¤ÏÀµ¤·¤¯¸¡½Ð¤Ç¤¤Ê¤¤¾ì¹ç¤¬¤¢¤ë¡£¤½¤³¤Ç¡¢²æ¡¹¤Ï¥Í¥Ã¥È¤Î³Ê»ÒÅÀ¤ËÂбþ¤¹¤ë²èÁü¤ÎÇ»ÅÙÃͤòÊÑÆ°¤µ¤»¤ë¼êË¡¤òÄó°Æ¤¹¤ë¡£¤³¤ì¤Ë¤è¤ê¡¢»¨²»¤Î±Æ¶Á¤ò·Ú¸º¤·¡¢»¨²»¤ò²óÈò¤¹¤ë¤³¤È¤¬²Äǽ¤Ç¤¢¤ë¤³¤È¤ò¡¢¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¼Â¸³¤Î·ë²Ì¤«¤é¼¨¤¹¤³¤È¤¬¤Ç¤¤¿¡£¤µ¤é¤Ë¡¢ÆþÎϲèÁü¤ËÂФ·¤Æ·«¤êÊÖ¤·¥Ñ¥¿¡¼¥ó²èÁü¤ò²Ã»»¤·¡¢¤½¤Î²èÁü¤ËÂФ·¤Æ½¾Íè¼êË¡¤òŬÍѤ·¤¿¡£¤½¤Î·ë²Ì¡¢¥¿¡¼¥²¥Ã¥ÈÊ᪤ξõ¶·¤¬ÊѤï¤ë²ÄǽÀ¤¬¤¢¤ë¤³¤È¤¬¼¨¤»¤¿¡£ |
Âê̾ | ·ëÂ÷¹¶·âÂÑÀ¤òͤ¹¤ëJPEG 2000¤Î³¬ÁØÀ¤òÊÝ»ý¤·¤¿¥¢¥¯¥»¥¹À©¸æ·¿°Å¹æ²½Ë¡ |
Ãø¼Ô | ¡ûº£Àô ¾Í»Ò(¿·³ã¸©¹©¶Èµ»½ÑÁí¹ç¸¦µæ½ê), Æ£µÈ ÀµÌÀ(¼óÅÔÂç³ØÅìµþ¥·¥¹¥Æ¥à¥Ç¥¶¥¤¥ó³ØÉô), °¤Éô ½Ê¿Í(¿·³ã¸©¹©¶Èµ»½ÑÁí¹ç¸¦µæ½ê), µ®²È ¿Î»Ö(¼óÅÔÂç³ØÅìµþ¥·¥¹¥Æ¥à¥Ç¥¶¥¤¥ó³ØÉô) |
Page | pp. 513 - 518 |
Keyword | °Å¹æ²½, JPEG 2000, ¥¢¥¯¥»¥¹À©¸æ, ¥Ï¥Ã¥·¥å´Ø¿ô, ·ëÂ÷¹¶·â |
Abstract | JPEG 2000 ¤Î½ÅÍפÊÆÃŤΰì¤Ä¤Ç¤¢¤ë³¬ÁØÀ¤òÊÝ»ý¤·¡¤¤«¤Ä¡¤½ÀÆð¤Ê¥¢¥¯¥»¥¹À©¸æ¤ò²Äǽ¤È¤·¤¿°Å¹æ²½Ë¡¤òÄó°Æ¤¹¤ë¡¥JPEG 2000 Éä¹æ²½²èÁü¤Ç¤Ï¡¤¥¹¥±¡¼¥é¥Ó¥ê¥Æ¥£¤òÍøÍѤ¹¤ë¤³¤È¤Ë¤è¤ê¡¤²èÁü¤ÎÍÎÁÇÛ¿®¤Ë¤ª¤¤¤Æ¡¤²Ý¶â¤Ë±þ¤¸¤¿¼Á¤Ç²èÁü¤ò¥æ¡¼¥¶¤ËÇÛ¿®¤¹¤ë¥¢¥¯¥»¥¹À©¸æ¤¬²Äǽ¤È¤Ê¤ë¡¥Äó°ÆË¡¤Ç¤Ï¡¤´ÉÍý¤¹¤ë°Å¹æ¸°¡Ê¥Þ¥¹¥¿¡¼¥¡¼¡Ë¤¬°ì¤Ä¤Ç¤¢¤ê¡¤¤¢¤ë»ØÄꤵ¤ì¤¿¼Á¤Î²èÁüºÆÀ¸¤òµöÂú¤µ¤ì¤¿¥æ¡¼¥¶¤ËÂФ·¤Æ¡¤¥Þ¥¹¥¿¡¼¥¡¼¤«¤é½¾Â°Åª¤ËÀ¸À®¤µ¤ì¤¿°ì¤Ä¤Î¸°¤òÇÛÁ÷¤¹¤ë¡¥¤Þ¤¿¡¤°Û¤Ê¤ë¼Á¤òµöÂú¤µ¤ì¤¿Â¾¤Î¥æ¡¼¥¶¤ËÂФ·¤Æ¤Ï¥Þ¥¹¥¿¡¼¥¡¼¤«¤é½¾Â°Åª¤Ë·èÄꤵ¤ì¤¿Â¾¤Î¸°¤òÇÛÁ÷¤¹¤ë¡¥²èÁü¤Î¼Á¤Î»ØÄê¤Ï¡¤JPEG2000 ¤¬¤â¤Ä¤¹¤Ù¤Æ¤Î¥¹¥±¡¼¥é¥Ó¥ê¥Æ¥£¤ËÂбþ¤¹¤ë¡¥¤µ¤é¤Ë¡¤Äó°ÆË¡¤Ï¡¤·ëÂ÷¹¶·â¤ËÂФ·¤ÆÂÑÀ¤òͤ·¡¤Ê£¿ô¤Î¥æ¡¼¥¶¤¬°Å¹æ¸°¤ò¶¦Í¤·¤Æ¤â¡¤µöÂú¤µ¤ì¤¿²è¼Á¤è¤ê¹â¤¤²è¼Á¤Ç¤ÎºÆÀ¸¤òº¤Æñ¤Ë¤¹¤ë¡¥ |
Âê̾ | ¶½Ê³À¥Ç¥£¥¸¥¿¥ëÈ¿±þ³È»¶¥·¥¹¥Æ¥à¤òÍѤ¤¤¿¥Ü¥í¥Î¥¤¿ÞÀ¸À® |
Ãø¼Ô | ¡û°ËÆ£ ¹¯°ì(ÅìËÌÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê), Ê¿ÄÍ âÃɧ(ÀçÂæÅÅÇȹ©¶È¹âÅùÀìÌç³Ø¹»), ÀÄÌÚ ¹§Ê¸(ÅìËÌÂç³ØÂç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê), Èõ¸ý ζͺ(ÅìË̹©¶ÈÂç³Ø¹©³ØÉô) |
Page | pp. 519 - 524 |
Keyword | È¿±þ³È»¶¥·¥¹¥Æ¥à, ·×»»´ö²¿³Ø, ¥Ü¥í¥Î¥¤¿Þ, ¥¹¥±¥ë¥È¥ó, ¶½Ê³À¥À¥¤¥Ê¥ß¥¯¥¹ |
Abstract | ËÜÏÀʸ¤Ç¤Ï¡¤¶½Ê³À¥Ç¥£¥¸¥¿¥ëÈ¿±þ³È»¶¥·¥¹¥Æ¥à¤òÍѤ¤¤¿¥Ü¥í¥Î¥¤¿ÞÀ¸À®¥¢¥ë¥´¥ê¥º¥à¤òÄó°Æ¤¹¤ë¡¥¶½Ê³ÀÈ¿±þ³È»¶¥À¥¤¥Ê¥ß¥¯¥¹¤Ë¤è¤êȯÀ¸¤Ç¤¤ë¶½Ê³ÇȤϡ¤¡ÖÅù®¤ÇÅÁȤ¹¤ë¡×¡¤¡Ö¾¤ÎÇȤȾ×Æͤ¹¤ë¤È¾ÃÌǤ¹¤ë¡×¤È¤¤¤¦À¼Á¤ò»ý¤Ã¤Æ¤¤¤ë¡¥¤³¤ÎÀ¼Á¤òÍøÍѤ¹¤ë¤³¤È¤Ç¡¤¶á˵¤Î2ÅÀ´Ö¤«¤éÅö¶¿Î¤¤Ë¤¢¤ëÀþ¤òÄ´¤Ù¤ë¤³¤È¤¬¤Ç¤¤ë¡¥ËÜÏÀʸ¤Ç¤Ï¡¤¤³¤ÎÀ¼Á¤òÍøÍѤ¹¤ë¤³¤È¤Ç¡¤·×»»´ö²¿³Ø¤ÎʬÌî¤Ç¤è¤¯°·¤ï¤ì¤ë¥Ü¥í¥Î¥¤¿Þ¤òÀ¸À®¤¹¤ë¤³¤È¤¬¤Ç¤¤ë¤³¤È¤ò¼¨¤¹¡¥¤Þ¤¿¡¤2¼¡¸µÊ¿Ì̾å¤ËÇÛÃÖ¤·¤¿ÅÀ·²¡¤´ö²¿Åª¤Ê¥Þ¥Ã¥×¡¤¼ê½ñ¤Ê¸»ú¤Ê¤É¤òÍѤ¤¤¿¼Â¸³¤Ë¤è¤ê¡¤¥Ü¥í¥Î¥¤¿Þ¤ä¥¹¥±¥ë¥È¥ó¤òÀ¸À®¤Ç¤¤ë¤³¤È¤ò¼¨¤¹¡¥ |
Âê̾ | ¥Õ¥ì¡¼¥àƱ´ü²Ã»»¤È¥Õ¥£¥ë¥¿¥ê¥ó¥°¤Ë¤è¤ë²ÏÀî¿å°Ì¸¡½Ð¥¢¥ë¥´¥ê¥º¥à |
Ãø¼Ô | ¡ûã·Æ£ ½ß»Ë, ´ä¶¶ À¯¹¨(Ĺ²¬µ»½Ñ²Ê³ØÂç³Ø¹©³ØÉôÅŵ¤·Ï) |
Page | pp. 525 - 530 |
Keyword | ²èÁüǧ¼±, ¥Õ¥£¥ë¥¿, ²ÏÀî¿å°Ì, ËÉºÒ |
Abstract | ¶áǯ¡¤½¸Ãæ¹ë±«¤ÎÁý²Ã¤Ë¤è¤ê²ÏÀîºÒ³²¤¬Â¿È¯¤·¤Æ¤¤¤ë¡¥Âкö¤È¤·¤Æ¤ÏÎÌ¿åÈĤòÍѤ¤¤¿¿å°Ì¸¡½ÐÊýË¡¤¬Äó°Æ¤µ¤ì¤Æ¤¤¤ë¤¬¡¤²ÏÀîÆâ¤Ø¤Î¹½Â¤Êª¤ÎÀßÃ֤ϲÏÀîË¡¤Ë¤è¤ê¸·¤·¤¯´ÉÍý¤µ¤ì¤Æ¤ª¤ê¹¥¤Þ¤·¤¯¤Ê¤¤¡¥¤½¤³¤ÇËÜÊó¹ð¤Ç¤Ï¡¤ÎÌ¿åÈĤòÀßÃÖ¤·¤Æ¤¤¤Ê¤¤²ÏÀî¤Î±ÇÁü¤Î¤ß¤Ç¿å°Ì¤ò¸¡½Ð¤¹¤ë¥¢¥ë¥´¥ê¥º¥à¤òÄó°Æ¤¹¤ë¡¥¤Þ¤º²ÏÀî±ÇÁü¤ËÂФ·¥Õ¥ì¡¼¥àƱ´ü²Ã»»¡¤Èùʬ½èÍý¤ò¹Ô¤¤¡¤¥¨¥Ã¥¸²èÁǤò¸¡½Ð¤¹¤ë¡¥¤½¤·¤Æ¥¨¥Ã¥¸²èÁǤβ£Êý¸þ¥Ò¥¹¥È¥°¥é¥à¤òºîÀ®¡¤¤½¤Î½ÄÊý¸þÀÑ»»ÃͤòÍѤ¤¤Æ¿å°Ì¸¡½Ð¤ò¹Ô¤¦¡¥Èùʬ½èÍý¤Ë¤Ä¤¤¤Æ¤Ï¡¤»þ¡¹¹ï¡¹¤ÈÊѲ½¤¹¤ë±ÇÁü¤´¤È¤ËºÇŬ¤Ê¥Õ¥£¥ë¥¿¤ÎÀß·×Ë¡¤òÄó°Æ¤¹¤ë¡¥¼Â¸³¤Î·ë²Ì¡¤ÌÜ»ë¿å°Ì¤ËÂФ·¤Æ¸íº¹10%¤Ç¤Î¿å°Ì¸¡½Ð¤¬³Îǧ¤µ¤ì¤¿¡¥ |
Âê̾ | JPEG2000¤Î¥¦¥§¡¼¥Ö¥ì¥Ã¥ÈÊÑ´¹¤ò³èÍѤ·¤¿²ÏÀî¿å°Ì¸¡½Ð¥¢¥ë¥´¥ê¥º¥à |
Ãø¼Ô | ¡ûº£°æ ͵Æó, ´ä¶¶ À¯¹¨(Ĺ²¬µ»½Ñ²Ê³ØÂç³Ø¹©³ØÉôÅŵ¤·Ï) |
Page | pp. 531 - 534 |
Keyword | ²èÁüǧ¼±, JPEG2000, ²ÏÀî, ËÉºÒ |
Abstract | ¶áǯ¡¢¿å³²¤¬Â¿È¯¤·¤Æ¤ª¤êËɺÒÂкö¤È¤·¤Æ¿å°Ì·×¤ä¥«¥á¥é±ÇÁü¤Ë¤è¤ë²ÏÀî´Æ»ë¤¬¹¤¯¼Â»Ü¤µ¤ì¤Æ¤¤¤ë¡£½¾ÍèË¡¤è¤ê¿å°Ì·×¤äÎÌ¿åÈĤòÀßÃÖ¤·¤Æ¿å°Ì¤ò·×¤ëÊýË¡¤¬¤¢¤ë¤¬¡¢¥³¥¹¥È¤ä²ÏÀîË¡¤Ë¤è¤ë²ÏÀî´ÉÍý¾å¤ÎÌäÂ꤬¤¢¤ë¡£¤½¤³¤ÇËÜÊó¹ð¤Ç¤Ï¡¢¥«¥á¥é±ÇÁü¤Î¤ß¤«¤éÎÌ¿åÈĤòÍѤ¤¤º¤Ëή¿å°è¤ò¸¡½Ð¤¹¤ë¥¢¥ë¥´¥ê¥º¥à¤òÄó°Æ¤¹¤ë¡£Äó°ÆË¡¤Ç¤Ï¡¢²ÏÀî´Æ»ë¥Ó¥Ç¥ª±ÇÁü¤ÎÉä¹æ²½ÅÁÁ÷¤ò¹Ô¤¦¤³¤È¤â¹Íθ¤·¤Æ¡¢²èÁü°µ½Ìµ»½Ñ¤Ç¤¢¤ëJPEG2000¤Î¥¦¥§¡¼¥Ö¥ì¥Ã¥ÈÊÑ´¹¤ò³èÍѤ·Î®¿åÉô¤ÈΦÉô¤ÎÆÃħÎ̤«¤éÎΰèȽÊ̤ò¹Ô¤¦¡£¤Þ¤¿¡¢¥Õ¥ì¡¼¥àƱ´ü²Ã»»¤òƳÆþ¤·¡¢Î®¿åÉô¤ÈΦÉô¤Ë¤ª¤±¤ëÆÃħÎ̤κ¹¤òÂ礤¯¤¹¤ë¤³¤È¤ÇȽÊÌÀºÅÙ¤ò¸þ¾å¤µ¤»¤ë¡£ |
Âê̾ | SOM¤Ë¤è¤ëƻϩɸ¼±ÆâÉôÎΰè¤ÎÃê½Ð½èÍý¤Î¸¡Æ¤ |
Ãø¼Ô | ¡û¿¢ÅÄ ÂóÌé, Ïɸ« °éμ(Ä»¼è´Ä¶Âç³ØÂç³Ø±¡´Ä¶¾ðÊó³Ø¸¦µæ²Ê), ÌùÌÚ ÅÐ(ÄÅ»³¹©¶È¹âÅùÀìÌç³Ø¹»), ¾¾Á° ¿Ê, Ê¡ËÜ Á±ÍÎ(Ä»¼è´Ä¶Âç³Ø´Ä¶¾ðÊó³ØÉô), Éû°æ ͵(Ä»¼èÂç³Ø¹©³ØÉô) |
Page | pp. 535 - 540 |
Keyword | ƻϩɸ¼±, ¼«¸ÊÁÈ¿¥²½¥Þ¥Ã¥×, ²èÁüǧ¼± |
Abstract | ¶áǯ¡¤Æ»Ï©¸òÄÌ¥·¥¹¥Æ¥à¤Ï¡¤¥¤¥ó¥Æ¥ê¥¸¥§¥ó¥È²½¤Ë¸þ¤±¤Æ¹âÅÙƻϩ¸òÄÌ¥·¥¹¥Æ¥à(Intelligent Transport System : ITS)¤Ø¤Î°Ü¹Ô¤¬¶¯¤¯´üÂÔ¤µ¤ì¤Æ¤¤¤ë¡¥ITS¤Î¥·¥¹¥Æ¥à¤ÎÃæ¤Ç¡¤°ÂÁ´±¿Å¾¤Î»Ù±ç¤È¤¤¤Ã¤¿¥Æ¡¼¥Þ¤¬¤¢¤ë¡¥¼Öξ¥É¥é¥¤¥Ð¡¼¤Ï¾ï¤ËÁö¹Ô´Ä¶Ç§¼±¤È¼Öξ¤ÎÀ©¸æ¤ò¹Ô¤ï¤Ê¤±¤ì¤Ð¤Ê¤é¤Ê¤¤¡¥¤½¤³¤Ç¡¤¸«Íî¤È¤µ¤ì¤¬¤Á¤Êƻϩɸ¼±¤òµ¡³£¤¬¼«Æ°Åª¤Ë¸¡½Ð¡¤Ç§¼±¤¹¤ë¥·¥¹¥Æ¥à¤¬¤Ç¤¤ì¤Ð¡¤¥É¥é¥¤¥Ð¡¼¤ÎÉéô·Ú¸º¤Ë¤Ä¤Ê¤¬¤ë¡¥ËÜÏÀʸ¤Ç¤Ï¡¤¼«¸ÊÁÈ¿¥²½¥Þ¥Ã¥×¤òÍѤ¤¤¿ÎسÔÃê½Ð¤È¡¤É¸¼±¤ÎÆâÉôÎΰè¤ÎÃê½Ð¼êË¡¤Î¸¡Æ¤¤ò¹Ô¤Ã¤Æ¤¤¤ë¡¥ |
Âê̾ | SoCÂ絬ÌÏ¥¨¥ó¥Ù¥Ç¥Ã¥É¥á¥â¥ê¹â®¥¥ã¥é¥¯¥¿¥é¥¤¥º¼êË¡ |
Ãø¼Ô | ¡ûÂç¼ ¾»É§, ¶âËÜ ½Ó´ö, ÄÍËÜ ÈþÃÒ»Ò, ÇòÅÄ ¸÷Íø, ÃæÅç δ(¥ë¥Í¥µ¥¹¥Æ¥¯¥Î¥í¥¸) |
Page | pp. 541 - 546 |
Keyword | ¥á¥â¥ê¥³¥ó¥Ñ¥¤¥é, ¥¥ã¥é¥¯¥¿¥é¥¤¥º, LPE |
Abstract | ¶áǯ¤ÎSoCÀ߷פˤª¤¤¤Æ¤Ï¡¢Â¿¼ï¿Íͤʥá¥â¥ê¥³¥ó¥Ñ¥¤¥é¤òû´ü´Ö¤Ë¹âÀºÅÙ¤ÇÀ¸À®¤¹¤ë¤³¤È¤¬Í׵ᤵ¤ì¤Æ¤¤¤ë¡£²æ¡¹¤ÎÄó°Æ¤¹¤ë¥á¥â¥êÀ߷״Ķ¤Ç¤Ï¡¢ÀºÅÙ¤òÍî¤È¤µ¤º¤Ë¹â®¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¤ò¹Ô¤¦¤Î¤ËŬ¤·¤¿³¬ÁØRC¥Í¥Ã¥È¥ê¥¹¥È¤òÀ¸À®¤·¡¢Ã»´ü´Ö¤Ç¥¥ã¥é¥¯¥¿¥é¥¤¥º¤ò¹Ô¤¤¡¢¥á¥â¥ê¥é¥¤¥Ö¥é¥ê¤òÀ¸À®¤¹¤ë¤¿¤á¤Î¥á¥â¥ê¥³¥ó¥Ñ¥¤¥é¤ò¹½ÃÛ¤¹¤ë¡£ËܼêË¡¤Ï´û¤Ë90nmµé¤Î¥á¥â¥ê¥â¥¸¥å¡¼¥ë³«È¯¤ËŬÍѤµ¤ì¤Æ¤ª¤ê¡¢À߷פθúΨ²½¡¢¥é¥¤¥Ö¥é¥ê¤Î¹âÉʼÁ²½¤ËÂ礤¯´óÍ¿¤·¤Æ¤¤¤ë¡£ |
Âê̾ | ¥Á¥Ã¥×Æâ¤Ð¤é¤Ä¤¤ò¹Íθ¤·¤¿FPGAÆâÇÛÀþ¥â¥Ç¥ë¤Î¸¡Æ¤ |
Ãø¼Ô | ¡û¿ù¸¶ ÍÍý, ¹â̳ ʹů, ¾®ÎÓ Ï½Ê, ¾®Ìî»û ½¨½Ó(µþÅÔÂç³ØÂç³Ø±¡¾ðÊó³Ø¸¦µæ²ÊÄÌ¿®¾ðÊó¥·¥¹¥Æ¥àÀ칶) |
Page | pp. 547 - 552 |
Keyword | FPGA, ElmoreÃÙ±ä, ¤Ð¤é¤Ä¤, ÇÛÀþ¥â¥Ç¥ë |
Abstract | ËܹƤǤϡ¢ºÆ¹½À®¥Ç¥Ð¥¤¥¹¤Ç¤¢¤ëFPGA¤Ë¤ª¤¤¤Æ¡¢²æ¡¹¤ÎÄó°Æ¤¹¤ë ¥Á¥Ã¥×Æâ¤Ð¤é¤Ä¤¤òÊä½þ¤¹¤ë¼êË¡¤òÍѤ¤¤ëºÝ¤ÎÇÛÀþ·ÐÏ©¤ÎÊѹ¹ ¤Ë¤è¤ë¥ª¡¼¥Ð¡¼¥Ø¥Ã¥É¤Ë¤Ä¤¤¤Æ¹Í»¡¤ò¹Ô¤¦¡£ËܹƤDz¾Äꤷ¤Æ¤¤¤ë FPGA¤Î¥¢¡¼¥¥Æ¥¯¥Á¥ã¤Ç¤Ï½ÄÊý¸þ¤È²£Êý¸þ¤ÎÇÛÀþ¤Ç¤½¤ÎÍÆÎ̤¬ °Û¤Ê¤ê¡¢ÇÛÀþ·ÐÏ©¤Î¤È¤êÊý¤Ë¤è¤êÃÙ±äÃͤ¬ÊѲ½¤¹¤ë¡£¥È¥é¥ó¥¸¥¹¥¿ ¤ÎÀǽ¤Ð¤é¤Ä¤Éý¤ËÂФ··ÐÏ©¤ÎÊѹ¹¤Ë¤è¤ëÃÙ±äÃͤÎÊѲ½¤¬Â礤±¤ì ¤Ð¡¢¤Ð¤é¤Ä¤¤òÍøÍѤ·¤¿FPGA¤ÎÀǽ¤Î¸þ¾å¤¬¸«¹þ¤á¤Ê¤¯¤Ê¤ë¡£¤¤¤¯¤Ä¤«¤Î ÇÛÀþ·ÐÏ©¤Ë¤Ä¤¤¤Æ¤Ð¤é¤Ä¤Êä½þ¤Î͸úÀ¤Ë¤Ä¤¤¤Æ¸¡Æ¤¤ò¹Ô¤Ã¤¿¡£ |
Âê̾ | Åý·×ŪSTA¤ÎÀºÅÙ¸¡¾Ú¼êË¡ |
Ãø¼Ô | ¡û¾®ÎÓ ¹¨¹Ô(ÆüËÜ¥·¥Î¥×¥·¥¹(³ô)), ¾®Ìî ¿®Ç¤(¥¸¡¼¥À¥Ã¥È¡¦¥¤¥Î¥Ù¡¼¥·¥ç¥ó), º´Æ£ ¹â»Ë(Åìµþ¹©¶ÈÂç³Ø), ´ä°æ ÆóϺ((³ô)¿ôÍý¥·¥¹¥Æ¥à), ¶¶ËÜ ¾»µ¹(ÂçºåÂç³Ø) |
Page | pp. 553 - 558 |
Keyword | SSTA, ¥â¥ó¥Æ¥«¥ë¥í²òÀÏ |
Abstract | ËÜȯɽ¤Ç¤Ïº£¸å¹¹¤Ë¥¯¥í¡¼¥º¥¢¥Ã¥×¤µ¤ì¤ë¤ÈÌܤµ¤ì¤ëÅý·×ŪÀ߷פǡ¢É¬¿Ü¤È¤Ê¤ëÅý·×Ū¥¹¥¿¥Æ¥£¥Ã¥¯¥¿¥¤¥ß¥ó¥°¸¡¾Ú(STA)¤Ë±÷¤¤¤Æµý¼õ½ÐÍè¤ë͸úÀ¤Î¸¡¾Ú¼êË¡¤òÄó°Æ¤¹¤ë¡£ ½¾Íè¤Î¥³¡¼¥Ê¡¼¥Ù¡¼¥¹²òÀϤǤϡ¢¥¿¥¤¥ß¥ó¥°¤Î¼ý«¤¬º¤Æñ¤Ë¤Ê¤Ã¤Æ¤¤Æ¤¤¤ë¤¬¡¢²¾¤ËÅý·×Ū¥¹¥¿¥Æ¥£¥Ã¥¯¥¿¥¤¥ß¥ó¥°¸¡¾Ú¤ò¹Ô¤Ã¤¿¤È¤·¤Æ¤â¤½¤Î͸úÀ¤Ë´Ø¤¹¤ëÂηÏŪ¤Ê¾ðÊ󤬤ʤ«¤Ã¤¿¡£ Æä˥â¥ó¥Æ¥«¥ë¥í²òÀϤǤÎMAX±é»»¤Î·ë²Ì¤È¡¢·ë²Ì¤òÀµµ¬Ê¬ÉۤȲ¾Äꤷ¤Æµá¤á¤¿±é»»·ë²Ì¤È¤Îº¹Ê¬¤¬À¸¤¸¡¢ÃÙ±äÊâα¤Þ¤êͽ¬¤ÇÍ°ÕÀ¤Î¤¢¤ë¸íº¹¤¬È¯À¸¤¹¤ë²ÄǽÀ¤¬¤¢¤ë¡£ ËÜȯɽ¤Ç¤ÏÅý·×Ū¥¹¥¿¥Æ¥£¥Ã¥¯¥¿¥¤¥ß¥ó¥°¸¡¾Ú¤Ç¤Î²ÝÂê¤äÈá´ÑÀ¤ò¸«¶Ë¤á¤ë¤¿¤á¤Î¸¡¾Ú¼êË¡¤òÄó°Æ¤¹¤ë¡£MAX±é»»¤Ë¤ÆÀ¸¤¸¤ëº¹Ê¬¤ò¡¢¤¢¤ëÅý·×À©Ìó(£³¦Ò¤Ê¤É)¤Ë´ð¤Å¤Æ³½Ð¤·¡¢¤½¤Îº¹Ê¬¤Îɾ²Á¼êË¡¤òÄó°Æ¤¹¤ë¡£ |
Âê̾ | ÅÅήÊÑÆ°¤ËÃåÌܤ·¤¿¹ÈϰϤÊÀ½Â¤¡¦´Ä¶¤Ð¤é¤Ä¤Âбþ¥²¡¼¥ÈÃÙ±ä¥â¥Ç¥ë |
Ãø¼Ô | ¡û¿·³« ·ò°ì, ¶¶ËÜ ¾»µ¹(ÂçºåÂç³Ø ¾ðÊó²Ê³Ø¸¦µæ²Ê), ¹õÀî ÆØ((³ô) ȾƳÂÎÍý¹©³Ø¸¦µæ¥»¥ó¥¿¡¼), Èø¾å ¹§Íº(ÂçºåÂç³Ø ¾ðÊó²Ê³Ø¸¦µæ²Ê) |
Page | pp. 559 - 564 |
Keyword | ¥²¡¼¥ÈÃÙ±ä¥â¥Ç¥ë, À½Â¤¤Ð¤é¤Ä¤, ´Ä¶¤Ð¤é¤Ä¤ |
Abstract | ËܹƤǤϹÈϰϤÊÀ½Â¤¡¦´Ä¶¤Ð¤é¤Ä¤¤ËÂбþ¤·¤¿¥²¡¼¥ÈÃÙ±ä¥â¥Ç¥ë¤òÄó°Æ¤¹¤ë¡¥Äó°Æ¥â¥Ç¥ë¤ÏÅÅήÊÑÆ°¤¬ÃÙ±ä¤ËÍ¿¤¨¤ë±Æ¶Á¤ò½ÐÎÏÉé²Ù¤ÎÃÖ´¹¤Çɽ¸½¤¹¤ë¡¥Ä㥳¥¹¥È¤ÊDC²òÀϤˤè¤ê¹½ÃÛ¤µ¤ì¤ëÅÅή¥â¥Ç¥ë¤òÍѤ¤¤ë¤³¤È¤Ç¡¤¤Ð¤é¤Ä¤¤¬¤Ê¤¤¾ì¹ç¤ÎÃÙ±ä·×»»¼°¤ä¥Æ¡¼¥Ö¥ë¤ò¤½¤Î¤Þ¤ÞÍѤ¤¤ÆÂ礤ʤФé¤Ä¤¤ËÂбþ¤Ç¤¤ë¡¥¤Þ¤¿¡¤Äó°Æ¥â¥Ç¥ë¤ÏÅý·×Ū¥¿¥¤¥ß¥ó¥°²òÀÏ¡¤½¾Íè¤Î¥³¡¼¥Ê¡¼¥Ù¡¼¥¹¥¿¥¤¥ß¥ó¥°²òÀϤÎξÊý¤Ç»ÈÍѲÄǽ¤Ç¤¢¤ë. 90 nm¥×¥í¥»¥¹¤òÁÛÄꤷ¤¿¼Â¸³·ë²Ì¤«¤é¡¤Äó°Æ¥â¥Ç¥ë¤Ë¤è¤ê¥Á¥ã¥Í¥ëĹ¡¤ïçÃÍÅÅ°µ¡¤ÅŸ»ÅÅ°µ¡¤²¹Å٤ΤФé¤Ä¤¤ËÂФ·¤Æ¥²¡¼¥ÈÃٱ䤬Àµ³Î¤Ë¸«ÀѤâ¤é¤ì¤ë¤³¤È¤òÌÀ¤é¤«¤Ë¤·¤¿¡¥¤Þ¤¿¡¤RCÉé²Ù¡¤¤æ¤ë¤ä¤«¤ÊÆþÎÏÁ«°ÜÇÈ·Á¤Ë¤âŬÍѤǤ¤ë¤³¤È¤ò³Îǧ¤·¤¿¡¥ |
Âê̾ | (¾·ÂÔ)¤Ð¤é¤Ä¤¤ò¹îÉþ¤¹¤ëÀß·×µ»½Ñ |
Ãø¼Ô | ¡û¾®Ìî»û ½¨½Ó(µþÅÔÂç³Ø) |
Page | pp. 565 - 570 |
Keyword | À½Â¤Íưײ½Àß·×, ¤Ð¤é¤Ä¤, Åý·×ŪÃÙ±ä²òÀÏ, DFM |
Abstract | ¤Þ¤º¡¢3À¤Âå¤Î¥×¥í¥»¥¹¤Ë¤ª¤±¤ë¤Ð¤é¤Ä¤¤ò¾Ò²ð¤·¡¢ÈùºÙ²½¤Ëȼ¤¤¤Ð¤é¤Ä¤¤ÎÅý·×ŪÀ¼Á¤¬Âç°èŪ¤ÊÊÑÆ°¤«¤é¶É½êŪ¤ÊÊÑÆ°¤ËÊѤï¤Ã¤Æ¤¤¤ë¤³¤È¤òÀâÌÀ¤¹¤ë¡£¼¡¤Ë¡¢¥È¥é¥ó¥¸¥¹¥¿¤ÈÇÛÀþ¤Ë¤Ä¤¤¤Æ¤Ð¤é¤Ä¤¤òºÆ¸½¤¹¤ëÊýË¡¤òÀâÌÀ¤¹¤ë¡£¤Þ¤¿¡¢¤³¤ì¤é¤Î¤Ð¤é¤Ä¤¤¬²óÏ©ÆÃÀ¤ËµÚ¤Ü¤¹±Æ¶Á¤ò¸¡Æ¤¤¹¤ë¡£ºÇ¸å¤Ë¡¢¤Ð¤é¤Ä¤¤ò¹îÉþ¤¹¤ë¤¿¤á¤ÎÀß·×µ»½Ñ¤È¤·¤Æ¡¢Åý·×ŪÃÙ±ä²òÀϵ»½Ñ¡¢µ¬Â§À¤ÎƳÆþ¤Ë¤è¤ë¤Ð¤é¤Ä¤¤ÎÀ©¸æ¡¢¥×¥í¥°¥é¥Þ¥Ö¥ë¥¢¥ì¡¼¹½Â¤¤òÍѤ¤¤¿¤Ð¤é¤Ä¤¤ÎÊä½þµ»½Ñ¤Ë¤Ä¤¤¤Æ¾Ò²ð¤¹¤ë¡£ |
Âê̾ | ¥»¥ë¥¢¥ì¥¤·¿¼«¸ÊºÆ¹½À®¥Ç¥Ð¥¤¥¹¤ÎÀ߷׸¡Æ¤¤Î¤¿¤á¤Î¥·¥ß¥å¥ì¡¼¥·¥ç¥ó´Ä¶ |
Ãø¼Ô | ¡û¿À»³ ¿¿°ì(µþÅÔÂç³ØÂç³Ø±¡ ¾ðÊó³Ø¸¦µæ²Ê ÄÌ¿®¾ðÊó¥·¥¹¥Æ¥àÀ칶), Àô ÃÎÏÀ(Ω̿´ÛÂç³Ø Íý¹©³ØÉô ÅŻҾðÊó¥Ç¥¶¥¤¥ó³Ø²Ê), ±ÛÃÒ ÍµÇ·, Ãæ¼ ¹Ô¹¨(µþÅÔÂç³ØÂç³Ø±¡ ¾ðÊó³Ø¸¦µæ²Ê ÄÌ¿®¾ðÊó¥·¥¹¥Æ¥àÀ칶) |
Page | pp. 571 - 576 |
Keyword | ¥Ç¥Ð¥¤¥¹Î³ÅÙ, ¥¢¡¼¥¥Æ¥¯¥Á¥ã¸¡Æ¤, ¥¢¡¼¥¥Æ¥¯¥Á¥ã¥â¥Ç¥ë, ưŪɾ²Á |
Abstract | ¼«¸ÊºÆ¹½À®¥Ç¥Ð¥¤¥¹¤ÎÀǽ¤ÏÍÍ¡¹¤Ê¥Õ¥¡¥¯¥¿¤ä¼Â¹Ô»þ¤Îͽ¬ÉÔǽ¤ÊµóÆ°¤Ëº¸±¦¤µ¤ì¤ë¤¿¤á¡¤¥¢¡¼¥¥Æ¥¯¥Á¥ã¸¡Æ¤Ãʳ¬¤ÇÀÅŪ¤ËÀǽɾ²Á¤ò¹Ô¤¦¤Î¤Ïº¤Æñ¤Ç¤¢¤ë¡¥ËܹƤǤϡ¤¼Â¥¢¥×¥ê¥±¡¼¥·¥ç¥ó¤òÍѤ¤¤¿¥·¥ß¥å¥ì¡¼¥·¥ç¥ó¥Ù¡¼¥¹¤Î¥¢¡¼¥¥Æ¥¯¥Á¥ãɾ²Á´Ä¶¤ò¹½ÃÛ¤·¤¿¡¥¤Þ¤¿Äó°Æ´Ä¶¤ÎŬÍÑÎã¤È¤·¤Æ¡¤Å¬±þŪÉé²Ùʬ»¶½èÍý¤òÍѤ¤¤¿É¾²Á¼Â¸³¤ò¹Ô¤¤¡¤³«È¯¤·¤¿´Ä¶¤ÎÍÍÑÀ¤ò¼¨¤·¤¿¡¥ |
Âê̾ | Simulated AnnealingË¡¤Ë¤è¤ëưŪºÆ¹½À®²Äǽ¥×¥í¥»¥Ã¥µ¤Î¤¿¤á¤Î¥¿¥¹¥¯Ê¬³äºÇŬ²½¥¢¥ë¥´¥ê¥º¥à |
Ãø¼Ô | ¡ûë¸ý °ìÅ°, ¾åÅÄ ¶³»Ò, ºä¼ç ·½»Ë, ÉðÆâ ÎÉŵ, º£°æ Àµ¼£(ÂçºåÂç³Ø Âç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê ¾ðÊó¥·¥¹¥Æ¥à¹©³ØÀ칶) |
Page | pp. 577 - 582 |
Keyword | ưŪºÆ¹½À®²Äǽ¥×¥í¥»¥Ã¥µ, ¥¿¥¹¥¯Ê¬³ä, Áȹ礻ºÇŬ²½ÌäÂê, Simulated AnnealingË¡ |
Abstract | ưŪºÆ¹½À®²Äǽ¥×¥í¥»¥Ã¥µ¤È¤Ï, Æ°ºî»þ¤Ë²óÏ©¤Î¹½À®¤ò½Ö»þ¤ËÊѹ¹¤Ç¤¤ë¥×¥í¥»¥Ã¥µ¤Ç¤¢¤ê, ¤µ¤Þ¤¶¤Þ¤ÊʬÌî¤Ø¤Î±þÍѤ¬´üÂÔ¤µ¤ì¤Æ¤¤¤ë¥×¥í¥»¥Ã¥µ¤Ç¤¢¤ë. ¤¢¤ë¥¿¥¹¥¯¤òưŪºÆ¹½À®²Äǽ¥×¥í¥»¥Ã¥µ¤Ç¹Ô¤¦¾ì¹ç, ¤Þ¤º¹Íθ¤·¤Ê¤±¤ì¤Ð¤Ê¤é¤Ê¤¤¤³¤È¤Ï, ½ê˾¤Î¥¿¥¹¥¯¤Î²óÏ©¹½À®Ã±°Ì¤Ø¤Îʬ³ä¤Ç¤¢¤ë. ËܹƤǤÏ, ưŪºÆ¹½À®²Äǽ¥×¥í¥»¥Ã¥µ¥â¥Ç¥ë¤òÄê¤á, ºÆ¹½À®»þ¤ËȯÀ¸¤¹¤ë¥á¥â¥ê¥¢¥¯¥»¥¹¤â¹Íθ¤·¤¿¥¿¥¹¥¯Ê¬³äºÇŬ²½¥¢¥ë¥´¥ê¥º¥à¤ò¼¨¤¹. ɾ²Á¼Â¸³¤è¤ê, 12¼ïÎà¤ÎưŪºÆ¹½À®²Äǽ¥×¥í¥»¥Ã¥µ¤Î¥¢¡¼¥¥Æ¥¯¥Á¥ã¤ËÂФ·, ºÇŬ²ò¤ÈƱ¤¸ÉʼÁ¤Î²ò¤¬Èó¾ï¤Ëû»þ´Ö¤ÇÆÀ¤é¤ì¤ë¤³¤È¤¬³Îǧ¤Ç¤¤¿. |
Âê̾ | ¥¢¥×¥ê¥±¡¼¥·¥ç¥ó¥×¥í¥»¥Ã¥µ¤Î¥Ç¡¼¥¿¥¥ã¥Ã¥·¥å¹½À®ºÇŬ²½¼êË¡ |
Ãø¼Ô | ¡ûËÙÆâ °ì±û, ¾®¸¶ ½Ó°ï, ¸ÍÀî ˾, Ìøß· À¯À¸, ÂçÉí äÉ×(Áá°ðÅÄÂç³ØÍý¹©³ØÉô¥³¥ó¥Ô¥å¡¼¥¿¡¦¥Í¥Ã¥È¥ï¡¼¥¯¹©³Ø²Ê) |
Page | pp. 583 - 588 |
Keyword | ¥×¥í¥»¥Ã¥µ¥³¥¢, ¥¥ã¥Ã¥·¥å, ºÇŬ²½, ÁȤ߹þ¤ß¥·¥¹¥Æ¥à |
Abstract | ÁȤ߹þ¤ß¥·¥¹¥Æ¥à¤Ë¤ª¤¤¤ÆÆÃÄê¤Î¥¢¥×¥ê¥±¡¼¥·¥ç¥ó¤ËÆò½¤·¤¿¥×¥í¥»¥Ã¥µ¥³¥¢¤¬É¬ÍפȤʤ롥ÆÃ¤Ë¥×¥í¥»¥Ã¥µ¥³¥¢¤Î¥¥ã¥Ã¥·¥å¤ËÃíÌܤ·¤¿¤È¤¡¤ÁȤ߹þ¤ß¥·¥¹¥Æ¥à¤Ç¤ÏÌÌÀÑÀ©Ì󤬸·¤·¤¤¤¿¤á¼Â¹Ô»þ´ÖÀ©Ìó¤òËþ¤¿¤¹Ãæ¤Ç¥á¥â¥ê¥µ¥¤¥ººÇ¾®¤«¤Ä¤è¤êñ½ã¤Ê¥¥ã¥Ã¥·¥å¹½À®¤òÆÀ¤ë¤³¤È¤¬¶¯¤¯Ë¾¤Þ¤ì¤ë¡¥ËܹƤǤÏÊ£¿ô¤Î¥¥ã¥Ã¥·¥å¹½À®¤ÎÃ椫¤é¥¢¥×¥ê¥±¡¼¥·¥ç¥ó¤ËŬ¤·¤¿¹½À®¤òÁªÂò¤¹¤ë¥¥ã¥Ã¥·¥å¹½À®ºÇŬ²½¥·¥¹¥Æ¥à¤òÄó°Æ¤¹¤ë¡¥¥¥ã¥Ã¥·¥å¹½À®ºÇŬ²½¥·¥¹¥Æ¥à¤Ï¥¥ã¥Ã¥·¥å¹½À®ºÇŬ²½¥¢¥ë¥´¥ê¥º¥à¤È¥¥ã¥Ã¥·¥åÀǽɾ²Á·Ï¤«¤é¹½À®¤µ¤ì¤ë¡¥¥¥ã¥Ã¥·¥å¹½À®ºÇŬ²½¥¢¥ë¥´¥ê¥º¥à¤ÏÊ£¿ô¤Î¥¥ã¥Ã¥·¥å·¿¡¤¥á¥â¥ê¥µ¥¤¥º¡¤¥Ö¥í¥Ã¥¯¥µ¥¤¥º¤òºÇŬ²½¤·¥¢¥×¥ê¥±¡¼¥·¥ç¥ó¤ËºÇŬ¤Ê¥¥ã¥Ã¥·¥å¹½À®¤òÁªÂò¤¹¤ë¡¥¥¥ã¥Ã¥·¥åÀǽɾ²Á·Ï¤Ï¥¥ã¥Ã¥·¥å¹½À®ºÇŬ²½¥¢¥ë¥´¥ê¥º¥à¤Ë¤ª¤¤¤Æ¥¥ã¥Ã¥·¥å¹½À®¤òÁªÂò¤¹¤ë¤¿¤á¤Î»Øɸ¤È¤·¤Æ¥á¥â¥ê¥¢¥¯¥»¥¹Í׵ᡤ¥á¥â¥êÀǽ¡¤¥¥ã¥Ã¥·¥å¹½À®¤«¤éÁí¥á¥â¥ê¥¢¥¯¥»¥¹»þ´Ö¤òµá¤á¤ë¡¥¥¥ã¥Ã¥·¥å¹½À®ºÇŬ²½¥¢¥ë¥´¥ê¥º¥à¤È¥¥ã¥Ã¥·¥åÀǽɾ²Á·Ï¤òϢư¤µ¤»¤ë¤³¤È¤ÇºÇŬ¤Ê¥¥ã¥Ã¥·¥å¹½À®¤òÆÀ¤ë¤³¤È¤¬²Äǽ¤È¤Ê¤ë¡¥É¾²Á¼Â¸³¤Ë¤è¤êÄó°Æ¥·¥¹¥Æ¥à¤Î͸úÀ¤ò³Îǧ¤·¤¿¡¥ |
Âê̾ | Dual-Rail Two-Phase Asynchronous Datapath Synthesis Based on Aggressive Register Sharing Model |
Ãø¼Ô | ¡ûKoji Ohashi, Mineo Kaneko(ËÌΦÀèü²Ê³Øµ»½ÑÂç³Ø±¡Âç³Ø) |
Page | pp. 589 - 594 |
Keyword | Asynchronous systems, Datapath synthesis, Resource sharing, Dual-rail two-phase style |
Abstract | This paper discusses a model for resource sharing, especially register sharing, in dual-rail two-phase asynchronous datapath synthesis. We introduce a new type of register which is driven by data to be latched and a control signal. The register latches input data by the state transition of the data itself and the transition of the control signal. By using these registers, multiple data can share a same register aggressively in a dual-rail two-phase asynchronous datapath. The main advantage of our register and register sharing model is to provide (1) datapaths with the reduced number of registers and demultiplexers, while keeping higher-speed, and (2) a larger solution space of resource sharing. |
Âê̾ | ¿®¹æ¤Î¾õÂÖÁ«°Ü¤Ë´ð¤Å¤¯¥Ï¡¼¥É¥¦¥¨¥¢¸¡¾Ú¤Î¤¿¤á¤Î¾õÂÖÁ«°Üʬ³ä¼êË¡ |
Ãø¼Ô | ¡û¹âÌî ¸÷»Ê, ÂçÄí ¿®Ç·, ºä¸ý ²Â̱(ÆüËÜ¥¢¥¤¡¦¥Ó¡¼¡¦¥¨¥à¡Ê³ô¡ËÅìµþ´ðÁø¦µæ½ê) |
Page | pp. 595 - 600 |
Keyword | ¥ê¥¢¥ë¥¿¥¤¥à¼Âµ¡¸¡¾Ú, ¥×¥í¥È¥¿¥¤¥×¸¡¾Ú |
Abstract | ¥·¥¹¥Æ¥à¥Æ¥¹¥È¤Î¸¡¾Ú»þ´Ö¤ò¹â®²½¤¹¤ë¤¿¤á¤Ë¡¢¥×¥í¥È¥¿¥¤¥Ô¥ó¥°¤ä¼Âµ¡¤òÍѤ¤¤¿¸¡¾Ú¤¬ÍѤ¤¤é¤ì¤Æ¤¤¤ë¤¬¡¢¿®¹æ¤Î²Ä´Ñ¬À¤¬Ä㤤¤¿¤á¡¢¥Æ¥¹¥È»þ¤ËȯÀ¸¤·¤¿ÌäÂê¤Î¡¢È¯À¸¾ò·ï¤ÎÆÃÄ꤬º¤Æñ¤Ç¤¢¤ë¡£¥×¥í¥È¥¿¥¤¥Ô¥ó¥°¤ä¼Âµ¡¤Ç¤Î¹â®¡¦ÂçÎ̤ο®¹æÊѲ½¤ò¿®¹æÁ«°Ü¤Îñ°Ì¤ÇÀÚ¤êʬ¤±¡¢¥È¥é¥ó¥¶¥¯¥·¥ç¥ó¤È¤·¤Æª¤¨¡¢¤½¤ÎȯÀ¸ÉÑÅÙ¾ðÊ󤫤鵩¤ÊÆ°ºî¤äÀß·×¼Ô¤ÎÁÛÄꤷ¤Æ¤¤¤Ê¤¤µóÆ°¤òʬÀϤ·¡¢¥Ï¡¼¥É¥¦¥¨¥¢¸¡¾Ú¤Î¸úΨ¤ò¸þ¾å¤µ¤»¤ë¼êË¡¤¬Äó°Æ¤µ¤ì¤Æ¤¤¤ë¡£¤·¤«¤·¡¢¥È¥é¥ó¥¶¥¯¥·¥ç¥ó¤òÀÚ¤ê½Ð¤¹¾ò·ï¤¬¤¢¤é¤«¤¸¤á»ÈÍѼԤ˼«ÌÀ¤Ç¤Ê¤±¤ì¤ÐŬÍѤǤ¤Ê¤¤¡£ËÜÏÀʸ¤Ç¤Ï¡¢Â¬ÄêÂоݤο®¹æÁ«°Ü¤«¤é¥È¥é¥ó¥¶¥¯¥·¥ç¥ó¤òÀڤ뤿¤á¤ÎʬΥ¾ò·ï¤ò¼«Æ°Åª¤ËȽÊ̤¹¤ë¼êË¡¤Ë¤Ä¤¤¤Æ½Ò¤Ù¤ë¡£ |
Âê̾ | ¥Þ¥ë¥Á¥Õ¥¡¥ó¥¯¥·¥ç¥ó±é»»´ï¤ò¹Íθ¤·¤¿±é»»¤Î¥Á¥§¥¤¥Ë¥ó¥°¼êË¡ |
Ãø¼Ô | ¡ûÄçÊý µ£(¶å½£Âç³Ø Âç³Ø±¡¥·¥¹¥Æ¥à¾ðÊó²Ê³ØÉÜ), ¾¾±Ê ͵²ð(¶å½£Âç³Ø Âç³Ø±¡¥·¥¹¥Æ¥à¾ðÊó²Ê³Ø¸¦µæ±¡) |
Page | pp. 601 - 606 |
Keyword | Æ°ºî¹çÀ®, ±é»»¤Î¥Á¥§¥¤¥Ë¥ó¥°, ¥Þ¥ë¥Á¥Õ¥¡¥ó¥¯¥·¥ç¥ó±é»»´ï |
Abstract | Æ°ºî¹çÀ®¤Ë¤ª¤¤¤Æ½¾Íè¤Î±é»»¤Î¥Á¥§¥¤¥Ë¥ó¥°¼êË¡¤Ç¤Ï¡¢ »ÈÍѤ¹¤ë±é»»´ï¤Ï²Ã»»´ï¤Ê¤É¤Îñ°ì¤Îµ¡Ç½¤òͤ¹¤ë±é»»´ï ¤·¤«ÍѤ¤¤é¤ì¤Æ¤¤¤Ê¤«¤Ã¤¿¡£ ËÜÏÀʸ¤Ç¤Ï¡¢Ê£¿ô¤Îµ¡Ç½¤òÀÚ¤êÂؤ¨²Äǽ¤Ê ¥Þ¥ë¥Á¥Õ¥¡¥ó¥¯¥·¥ç¥ó±é»»´ï¤ò¥Á¥§¥¤¥Ë¥ó¥°¤ÎºÝ¤Ë¹Íθ¤¹¤ë¤³¤È¤Ç¡¢ ½¾Íè¤è¤ê¤â¥ì¥¤¥Æ¥ó¥·¤¬ºï¸º²Äǽ¤Ê¼êË¡¤òÄó°Æ¤¹¤ë¡£ Äó°Æ¼êË¡¤Ï¡¢ÌäÂê¤ò0/1À°¿ôÀþ·Á·×²èÌäÂê¤È¤·¤Æ Äê¼°²½¤¹¤ë¤³¤È¤Ç¡¢»ñ¸»À©ÌóµÚ¤ÓÆ°ºî¼þÇÈ¿ôÀ©Ìó²¼¤Ç ¥ì¥¤¥Æ¥ó¥·¤¬ºÇ¾®¤È¤Ê¤ë±é»»´ï¥»¥Ã¥ÈµÚ¤Ó¥¹¥±¥¸¥å¡¼¥ë¤ò µá¤á¤ë¤³¤È¤ò²Äǽ¤È¤¹¤ë¡£ ¼Â¸³¤Ç¤Ï¡¢Äó°Æ¼êË¡¤¬Í¸ú¤Ç¤¢¤ë¤³¤È¤¬³Îǧ¤µ¤ì¤¿¡£ |
Âê̾ | Æ°ºî¹çÀ®¤Ë¤ª¤±¤ë´Ø¿ô¸Æ½Ð¤·¤ÎºÇŬ²½ |
Ãø¼Ô | ¡û¸¶ Í´»Ò, ÉÚ»³ ¹¨Ç·, ËÜÅÄ ¿¸Ìé, ¹âÅÄ ¹¾Ï(̾¸Å²°Âç³Ø Âç³Ø±¡¾ðÊó²Ê³Ø¸¦µæ²Ê) |
Page | pp. 607 - 612 |
Keyword | Æ°ºî¹çÀ®, ´Ø¿ô¸Æ½Ð¤·, À°¿ô·×²èÌäÂê |
Abstract | ËÜÏÀʸ¤Ç¤Ï¡¢Æ°ºî¹çÀ®¤Ë¤ª¤±¤ë´Ø¿ô¸Æ½Ð¤·¤ÎºÇŬ²½¼êË¡¤òÄó°Æ¤¹¤ë¡£Äó°Æ¼êË¡¤Ï¡¢Ê£¿ô¤Î´Ø¿ô¤«¤é¹½À®¤µ¤ì¤ë¥×¥í¥°¥é¥à¤òÂоݤȤ·¤Æ¡¢¥¤¥ó¥é¥¤¥óŸ³«¤¹¤ë´Ø¿ô¤È¥¤¥ó¥é¥¤¥óŸ³«¤·¤Ê¤¤´Ø¿ô¤ÎºÇŬ¤ÊÁȹ礻¤ò·èÄꤹ¤ë¡£¤Þ¤¿¡¢Ê£¿ô¤Î´Ø¿ô¤ò£±¤Ä¤ËÊ»¹ç¤¹¤ë¤³¤È¤Ë¤è¤ê¡¢»ñ¸»¤Î¶¦Í¤ò¼Â¸½¤¹¤ë¡£ËÜÏÀʸ¤Ç¤Ï¡¢´Ø¿ô¸Æ½Ð¤·¤ÎºÇŬ²½¼êË¡¤Î³µÎ¬¤òÀâÌÀ¤·¤¿¸å¡¢¤³¤ÎºÇŬ²½ÌäÂê¤òÀ°¿ô·×²èÌäÂê¤È¤·¤ÆÄê¼°²½¤¹¤ë¡£ºÇ¸å¤Ë¡¢¼Â¸³¤Ë¤è¤ê½¾Íè¼êË¡¤ËÂФ¹¤ëÍ¥°ÌÀ¤ò¼¨¤¹¡£ |
Âê̾ | Tri-Connectivity Augmentation Problems for Bi-connected Graphs with Upper Bounds on Vertex-Degree Increase |
Ãø¼Ô | Takanori Fukuoka, Satoshi Taoka(Graduate School of Engineering, Hiroshima University), ¡ûToshiya Mashima(Hiroshima International University), Toshimasa Watanabe(Graduate School of Engineering, Hiroshima University) |
Page | pp. 613 - 618 |
Keyword | graphs, connectivity augmenation, vertex-connectivity, degree constrains |
Abstract | The 3-vertex-connectivity augmentation problem of a graph with degree constraints, 3VCA-DC, is defined as follows: ``Given an undirected graph G=(V,E) and an upper bound a(v;G) ¢º Z+ ¢À ¡ç on vertex-degree increase for each v\in V, find a smallest set E' of edges such that (V,E ¢À E') has at least three internally-disjoint paths between any pair of vertices in V and such that vertex-degree increase of each v ¢º V by the addition of E' to G is at most a(v;G), where Z+ is the set of nonnegative integers.'' In this paper we show that finding an optimum solution to 3VCA-DC for a bi-connected graph G can be done in O(|V||V|+|E|) time. |
Âê̾ | System-Level Diagnosis in the Presence of Intermittent Faults |
Ãø¼Ô | Daisuke Kiri, ¡ûToshinori Yamada(ºë¶ÌÂç³ØÂç³Ø±¡ Íý¹©³Ø¸¦µæ²Ê ¿ôÍýÅŻҾðÊóÉôÌç) |
Page | pp. 619 - 624 |
Keyword | System-Level Diagnosis, Intermittent Faults |
Abstract | Fu and Beigel introduced a graph-theoretical model for a system diagnosis in the presence of intermittent faults, which we call the FB model. This paper gives a necessary and sufficient condition for a digraph to be diagnosable in the FB model, and presents two algorithms for a system diagnosis in the presence of intermittent faults. |
Âê̾ | (¾·ÂÔ)¥â¥Ç¥ë¸¡ºº¤òÍѤ¤¤¿¥¿¥°VLAN¤ÎÀßÄ긡ºº |
Ãø¼Ô | ¡ûݯÅÄ ±Ñ¼ù(NTT¥³¥ß¥å¥Ë¥±¡¼¥·¥ç¥ó²Ê³Ø´ðÁø¦µæ½ê ¿Í´Ö¾ðÊ󸦵æÉô ¾ðÊó´ðÁÃÍýÏÀ¸¦µæ¥°¥ë¡¼¥×) |
Page | pp. 625 - 630 |
Keyword | ¥Í¥Ã¥È¥ï¡¼¥¯, ¸¡ºº, LAN, ¥â¥Ç¥ë¸¡ºº, ÍÍÁêÏÀÍý |
Abstract | ¥Í¥Ã¥È¥ï¡¼¥¯µ¡´ï¤ÎÀßÄê¤ÏÄ̾ï¿Í¼ê¤Ë¤è¤Ã¤Æ¹Ô¤ï¤ì¤ë. ¤³¤Î¤¿¤á, ÄÌ¿®¤ÎÃÇÀä¤ä¾ðÊó¤Îϳ±È¤Ê¤É¥Í¥Ã¥È¥ï¡¼¥¯¤Ë¿¼¹ï¤Ê¾ã³²¤ò¤â¤¿¤é¤¹ÀßÄê¥ß¥¹¤¬È¯À¸¤¹¤ë¤³¤È¤¬¤¢¤ë. ËܹƤǤϥͥåȥ¥¯µ¡´ï, Æä˥¿¥°VLAN¤òÍѤ¤¤ëEthernetµ¡´ï¤ÎÀßÄê¤ÎÀµ¤·¤µ¤ò¥â¥Ç¥ë¸¡ººË¡¤òÍѤ¤¤Æ¸¡ºº¤¹¤ëÊýË¡¤òÄó°Æ¤¹¤ë. ¤³¤ÎÊýË¡¤Ë¤è¤ê, ¥Í¥Ã¥È¥ï¡¼¥¯¤ËÍ׵ᤵ¤ì¤ëÍÍ¡¹¤ÊÀ¼Á¤ò¸úΨŪ¤Ë¸¡ºº¤Ç¤¤ë¤è¤¦¤Ê¤ë. ¤Þ¤¿, ÀßÄê¤Ë¸í¤ê¤¬¤¢¤ë¾ì¹ç¤Ë¤Ï, ¤³¤ÎÊýË¡¤Ë¤è¤êµ¯¤³¤êÆÀ¤ë²ÄǽÀ¤Î¤¢¤ë¾ã³²¤Ë¤Ä¤¤¤ÆÄ´¤Ù¤ë¤³¤È¤¬¤Ç¤¤ë. ¤³¤ì¤ÏÀßÄê¥ß¥¹¤ò½¤Àµ¤¹¤ëºÝ¤ËÊØÍø¤Ç¤¢¤ë. |
Âê̾ | Polynomial-Time Algorithm for Finding a Solution in the Core of a Multicommodity Flow Game |
Ãø¼Ô | Kazuhiro Karasawa, ¡ûToshinori Yamada(ºë¶ÌÂç³ØÂç³Ø±¡ Íý¹©³Ø¸¦µæ²Ê ¿ôÍýÅŻҾðÊóÉôÌç) |
Page | pp. 631 - 636 |
Keyword | Multicommodity flow game, Coalitional game, Core, Spider, Complete Graph |
Abstract | Motivated by the development of an efficient and stable routing scheme for the Internet, Papadimitriou introduced a multicommodity flow game and raised the problem of whether the core of a multicommodity flow game is always nonempty. Markakis and Saberi settled the problem affirmatively. However, thier proof is not constructive, and it is not known how to find a solution in the core of the game, to the best of my knowledge. This paper presents a polynomial-time algorithm for finding a multicommodity flow game if G is a spider or complege graph. |
Âê̾ | Performance Comparison of Algorithms for the Dynamic Shortest Path Problem |
Ãø¼Ô | Takashi Iguchi, ¡ûSatoshi Taoka, Daisuke Takafuji, Toshimasa Watanabe(Graduate School of Engineering, Hiroshima University) |
Page | pp. 637 - 642 |
Keyword | networks, shortest path problems, dynamic algorithms, static algorithms |
Abstract | A network in an edge-weighted directed graph and an edge operation is an operation that increases or decreases an edge weight. Decreasing an edge weight from an infinite value to a finite one or increasing an edge weight from a finite value to an infinite one, respectively, corresponds to addition or deletion of an edge. The dynamic shortest path problem(DSPP for short) is defined by ``Given any network, with a specified vertices, and any sequence of edge operations, construct a shortest path tree of each network obtained by executing those edge operations one by one in the order of the sequence.'' As an application, fast routing for an interior network using link state protocols, such as OSPF and IS-IS, requires efficiently solving DSPP. Based on experimental results on networks of large size and a lot of edge operations, the paper shows that NST(BF)+ proposed by Narvaez et.al in 2000 is the fastest among 25 existing algorithms that we have tried. Also shown is that dynamic algorithms are faster than repeating a static algorithm in solving DSPP. |