现代电子技术2013，Vol.36Issue(4)：133-135,140,4.
基于集成模糊神经网络的容差模拟电路故障诊断方法
Approach of tolerance analog circuit fault diagnosis based on integrated fuzzy neural network
摘要
Abstract
In order to solve the problem of tolerance analog circuit fault diagnosis, a fault diagnosis method based on an in-tegrated T-S fuzzy neural network was used. PSPICE software simulations is applied to get fault data, and then the wavelet de-composition and normalization of fault data are executed to obtain the neural network training samples. Finally, the samples are assigned to each T-S fuzzy neural network for training and testing. In the training process, the additional momentum BP algo-rithm, whose learning rate is variable, is used to train the network weight for making its stability and convergence speed best. The simulation results show that the approach has fast convergence and high accuracy. It can effectively realize the analog cir-cuits fault diagnosis.关键词
模糊神经网络/模拟电路故障诊断/集成神经网络/学习速率可变Key words
fuzzy neural network/analog circuit fault diagnosis/integrated neural network/learning rate variable分类
信息技术与安全科学引用本文复制引用
韩宝如,崔蕾..基于集成模糊神经网络的容差模拟电路故障诊断方法[J].现代电子技术,2013,36(4):133-135,140,4.基金项目
海南省自然科学基金资助项目(610231) （610231）
