Based on Compact Type of Wavelet Neural Network Tolerance Analog Circuit Fault Diagnosis

Author

Han, Baoru ; Wu, Hengyu

Author_Institution

Dept. of Electron. Eng., Hainan Software Profession Inst., Qionghai, China

fYear

2009

fDate

19-20 Dec. 2009

Firstpage

1

Lastpage

4

Abstract

Based on the classical wavelet neural network, this paper put forward a sort of improved multiple-input multiple-output compact type of wavelet neural network, adopted adaptive learning rate and additional momentum BP algorithm to carry out training, studied its tolerance analog circuit fault diagnosis applications. Simulation results displayed that the compact type of wavelet neural network learning is fast, it can be effective diagnosed and located to tolerance analog circuit fault.

Keywords

analogue circuits; backpropagation; circuit analysis computing; fault diagnosis; fault tolerance; neural nets; wavelet transforms; BP algorithm; adaptive learning rate; multiple-input multiple-output compact type; tolerance analog circuit fault diagnosis; wavelet neural network analog circuit fault diagnosis; Adaptive systems; Analog circuits; Circuit faults; Circuit simulation; Convergence; Fault diagnosis; Neural networks; Neurons; Radial basis function networks; Software algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4994-1

Type

conf

DOI

10.1109/ICIECS.2009.5363065

Filename

5363065