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Committee Date Time Place Paper Title / Authors Abstract Paper #
MBE, NC
(Joint)		 2015-12-19
13:00		 Aichi Nagoya Institute of Technology Limited General Regression Neural Network for embedded systems and its implementation method to increase its throughput
Daisuke Nishio, Koichiro Yamauchi (Chubu Univ.) NC2015-46		 Recent improvement of the microcomputer enables the execution of complex intelligent algorithms on embedded systems.

... [more]		 NC2015-46
pp.1-6
NC, MBE
(Joint)		 2014-03-18
15:00		 Tokyo Tamagawa University Modified limited General Regression Neural Network by introducing a page-replacement algorithm
Yusuke Kondo, Koichiro Yamauchi (Chubu Univ.) NC2013-112		 In our previous work, we had proposed a Limited General Regression Neural Netwrok (LGRNN), which continues incremental l... [more] NC2013-112
pp.139-143
MBE, NC
(Joint)		 2012-03-14
16:00		 Tokyo Tamagawa University Incremental Learning for regression on a budget
Koichiro Yamauchi (Chubu Univ) NC2011-145		 In our previous work, we had proposed a limited general regression neural network (LGRNN) for embedded systems.
The LGR... [more]		 NC2011-145
pp.141-146
NC, MBE
(Joint)		 2011-03-07
11:30		 Tokyo Tamagawa University Maximum Power Point Tracking Converter Using a Limited General Regression Neural Network
Koichiro Yamauchi (Chubu Univ) NC2010-134		 In this paper, we propose a limited general regression neural network (LGRNN) for embedded systems.
The LGRNN is an imp... [more]		 NC2010-134
pp.41-46
NC, MBE [detail] 2010-12-19
11:45		 Aichi Nagoya Univ. Limited General Regression Neural Networks
Koichiro Yamauchi (Chubu Univ.) MBE2010-71 NC2010-82		 An incremental learning method for the general regression neural network(GRNN) for embedded systems is proposed.
Althou... [more]		 MBE2010-71 NC2010-82
pp.91-96
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