计算机技术与发展Issue(3)：194-197,201,5.DOI:10.3969/j.issn.1673-629X.2014.03.048
基于改进LLE的Elman神经网络电路故障诊断
Research on OIF-Elman Neural Network Circuit Fault Diagnosis Based on Improved LLE
摘要
Abstract
The circuit is more and more complex and followed by a circuit system failure,so how to locate the fault occurs is a major problem. For improving the performance of fault diagnosis,use an improved locally linear embedding analysis method as the initial data ( raw data) processor for output response sequence to reduce the dimension and extract fault feature vector,and then through the OIF-El-man neural network to build fault classifier for fault detection circuit. Simulation results show that the fault diagnosis method is made of improved LLE and OIF-Elman neural network is not only to have the better diagnosis rate compared with the BP neural network,but also greatly enhance convergence speed for the whole network.关键词
定位故障/改进的局部线性分析/降维/OIF-Elman神经网络Key words
fault locating/improved locally linear embedding analysis/dimension reduction/OIF-Elman neural network分类
信息技术与安全科学引用本文复制引用
郭斌,齐金鹏..基于改进LLE的Elman神经网络电路故障诊断[J].计算机技术与发展,2014,(3):194-197,201,5.基金项目
国家自然科学基金资助项目(61104154) （61104154）
中央高校基本科研业务费专项资金 （）
