The Third Kind of Generalized Congruence Neural Network is Used to Diagnose Fault of Attitude Control System

摘要：

This paper uses generalized congruence function instead of transfer function of classical BP neural network, and improve convergence rate of neural network. We introduce the subsection generalized derivation, error back propagation derivation mechanism of classical BP algorithm to adjust weight vector in generalized congruence neural network, and modify generalized congruence neural network, and then can obtain the third kind of generalized congruence neural network (GCNN3). Finally, by means of fault diagnosis experiment of attitude control system, we compare approximation performance of the third kind of generalized congruence neural network with BP neural network; approximation effect and stable performance of GCNN3 is equivalent to BPNN, but convergence rate of the former is much faster than the latter.

关键词： generalized congruence Neural network, Fault diagnosis

作者: XU Yangmin XUE Lei WANG Keren XU Jiren LIU Jihai

作者单位: Department of information Eletric engineering institute of Hefei Hefei,China

会议类型: 国际会议

会议名称: 2011 3rd IEEE International Conference on Computer Research and Development(ICCRD 2011)(2011第三届计算机研究与发展国际会议)

会议地点: 上海

会议语种:英文

页码: 348-351

在线出版日期: 2011-03-11（万方平台首次上网日期，不代表论文的发表时间）