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Author:

Zuo, Lei (Zuo, Lei.) | Hou, Li-Gang (Hou, Li-Gang.) | Gao, Da-Ming (Gao, Da-Ming.) | Peng, Xiao-Hong (Peng, Xiao-Hong.) | Wu, Wu-Chen (Wu, Wu-Chen.) (Scholars:吴武臣)

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Abstract:

In order to address the problems of the conventional Wavelet Neural Network (WNN) in analog circuit fault diagnosis, a new method of analog circuit fault diagnosis, based on Wavelet Neural Network and particle swarm optimization (PSO-WNN), is proposed in this paper. A practical inspecting of a filter circuit has been implemented, using both the new and the conventional method. The experimental results indicate that the new method possess higher precision than WNN.

Keyword:

Analog circuits Fault detection Failure analysis Timing circuits Particle swarm optimization (PSO)

Author Community:

  • [ 1 ] [Zuo, Lei]VLSI and System Lab., Beijing University of Technology, Beijing 100022, China
  • [ 2 ] [Hou, Li-Gang]VLSI and System Lab., Beijing University of Technology, Beijing 100022, China
  • [ 3 ] [Gao, Da-Ming]VLSI and System Lab., Beijing University of Technology, Beijing 100022, China
  • [ 4 ] [Peng, Xiao-Hong]VLSI and System Lab., Beijing University of Technology, Beijing 100022, China
  • [ 5 ] [Wu, Wu-Chen]VLSI and System Lab., Beijing University of Technology, Beijing 100022, China

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Source :

Journal of Beijing University of Technology

ISSN: 0254-0037

Year: 2010

Issue: 3

Volume: 36

Page: 306-309

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: 10

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