Presentation 2017-03-02
An algorithm to compute covariance for finding distribution of the maximum
Daiki Azuma, Shuji Tsukiyama, Masahiro Fukui, Takashi Kambe,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) In statistical approaches such as statistical static timing analysis, the distribution of the maximum of plural distributions is computed by repeating a maximum operation for two distributions. Moreover, since each distribution is represented by a linear combination of several explanatory random variables so as to handle correlations efficiently, sensitivity of the maximum of two distributions to each explanatory random variable, that is, covariance between the maximum and an explanatory random variable, must be calculated in every maximum operation. However, if the distribution of the maximum is represented by a Gaussian or a Gaussian mixture model, it is not always possible to make both variance and covariance accurate values. We propose an algorithm to compute covariance with smaller error without deteriorating the accuracy of variance, and show experimental results to evaluate its performance.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) statistical maximum operation / Gaussian mixture model / covariance / sensitivity / statistical methods
Paper # VLD2016-121
Date of Issue 2017-02-22 (VLD)

Conference Information
Committee VLD
Conference Date 2017/3/1(3days)
Place (in Japanese) (See Japanese page)
Place (in English) Okinawa Seinen Kaikan
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Takashi Takenana(NEC)
Vice Chair Hiroyuki Ochi(Ritsumeikan Univ.)
Secretary Hiroyuki Ochi(Fujitsu Labs.)
Assistant Parizy Matthieu(Fujitsu Labs.)

Paper Information
Registration To Technical Committee on VLSI Design Technologies
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) An algorithm to compute covariance for finding distribution of the maximum
Sub Title (in English)
Keyword(1) statistical maximum operation
Keyword(2) Gaussian mixture model
Keyword(3) covariance
Keyword(4) sensitivity
Keyword(5) statistical methods
1st Author's Name Daiki Azuma
1st Author's Affiliation Chuo University(Chuo Univ.)
2nd Author's Name Shuji Tsukiyama
2nd Author's Affiliation Chuo University(Chuo Univ.)
3rd Author's Name Masahiro Fukui
3rd Author's Affiliation Ritsumeikan University(Ritsumeikan Univ.)
4th Author's Name Takashi Kambe
4th Author's Affiliation Kinki University(Kinki Univ.)
Date 2017-03-02
Paper # VLD2016-121
Volume (vol) vol.116
Number (no) VLD-478
Page pp.pp.103-108(VLD),
#Pages 6
Date of Issue 2017-02-22 (VLD)