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Author:

Wang, Jinhui (Wang, Jinhui.) | Zuo, Lei (Zuo, Lei.) | Gong, Na (Gong, Na.) | Gao, Daming (Gao, Daming.) | Geng, Shuqin (Geng, Shuqin.) | Zhang, Wang (Zhang, Wang.) | Hou, Ligang (Hou, Ligang.) | Peng, Xiaohong (Peng, Xiaohong.) | Wu, Wuchen (Wu, Wuchen.) (Scholars:吴武臣)

Indexed by:

CPCI-S

Abstract:

An approach for estimating the leakage power and the speed of the dual threshold domino OR, gates based on Wavelet Neural Networks (WNN) in 45 mm technology is proposed. The estimating system has fast convergence and high precision. By studying the impact of the dual threshold voltage technique (DTV) on leakage reduction and delay increase, it successfully estimates the nonlinear changing of the leakage power and delay of the different inputs domino OR gates. At last, the reason for the estimating error and the trend of the estimating curve are explained, respectively.

Keyword:

Dual threshold domino OR Leakage power Wavelet Neural Networks Speed

Author Community:

  • [ 1 ] [Wang, Jinhui]Beijing Univ Technol, VLSI, Beijing 100124, Peoples R China
  • [ 2 ] [Zuo, Lei]Beijing Univ Technol, VLSI, Beijing 100124, Peoples R China
  • [ 3 ] [Gao, Daming]Beijing Univ Technol, VLSI, Beijing 100124, Peoples R China
  • [ 4 ] [Geng, Shuqin]Beijing Univ Technol, VLSI, Beijing 100124, Peoples R China
  • [ 5 ] [Zhang, Wang]Beijing Univ Technol, VLSI, Beijing 100124, Peoples R China
  • [ 6 ] [Hou, Ligang]Beijing Univ Technol, VLSI, Beijing 100124, Peoples R China
  • [ 7 ] [Peng, Xiaohong]Beijing Univ Technol, VLSI, Beijing 100124, Peoples R China
  • [ 8 ] [Wu, Wuchen]Beijing Univ Technol, VLSI, Beijing 100124, Peoples R China
  • [ 9 ] [Gong, Na]Hebei Univ, Col Elect & Informat Engn, Baoding 071002, Peoples R China

Reprint Author's Address:

  • [Wang, Jinhui]Beijing Univ Technol, VLSI, Beijing 100124, Peoples R China

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Source :

ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 1, PROCEEDINGS

ISSN: 0302-9743

Year: 2009

Volume: 5551

Page: 844-,

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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