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Author:

Zuo, Lei (Zuo, Lei.) | Hou, Ligang (Hou, Ligang.) | Wu, Wuchen (Wu, Wuchen.) (Scholars:吴武臣) | Wang, Jinhui (Wang, Jinhui.) | Geng, Shuqin (Geng, Shuqin.)

Indexed by:

CPCI-S

Abstract:

A new method of analog IC fault diagnosis is proposed in this paper, which is based on wavelet neural network ensemble (WNNE) technique and Adaboost algorithm. This makes the way of the directory be of use in fault, and enhances the validity of the fault diagnosis. Using wavelet decomposition as a tool for extracting feature, Then, after training the WNNE by faulty feature vectors, the fault diagnosis of a radar scanning circuit is implemented with this new. method. The simulation results show that the new method is more effective than the traditional wavelet neural network (WNN) method.

Keyword:

Fault diagnosis Adaboost Wavelet neural network ensemble

Author Community:

  • [ 1 ] [Zuo, Lei]Beijing Univ Technol, VLSI & Syst Lab, Beijing 100022, Peoples R China
  • [ 2 ] [Hou, Ligang]Beijing Univ Technol, VLSI & Syst Lab, Beijing 100022, Peoples R China
  • [ 3 ] [Wu, Wuchen]Beijing Univ Technol, VLSI & Syst Lab, Beijing 100022, Peoples R China
  • [ 4 ] [Wang, Jinhui]Beijing Univ Technol, VLSI & Syst Lab, Beijing 100022, Peoples R China
  • [ 5 ] [Geng, Shuqin]Beijing Univ Technol, VLSI & Syst Lab, Beijing 100022, Peoples R China

Reprint Author's Address:

  • [Zuo, Lei]Beijing Univ Technol, VLSI & Syst Lab, Beijing 100022, Peoples R China

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Source :

ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 3, PROCEEDINGS

ISSN: 0302-9743

Year: 2009

Volume: 5553

Page: 772-779

Language: English

Cited Count:

WoS CC Cited Count: 1

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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