The Research on Identification for Electromagnetic Interference in Automobile Based on WPD and MLPNN

摘要：

The technique for recognizing and identifying disturbed signals based on wavelet packet decomposition (WPD) and multilayer perceptron neural network (MLPNN) was proposed. It was greatly reduced the volume of computation after Parsevals theorem energy rule and feature extraction of the disturbed signals emerged by the equipment called EM-Test which could bring confirmed automotive interferential signals on automobile. A neural network was also developed for fast interferences identification

关键词： electromagnetic compatibility wavelet packet decomposition multilayer perceptron neural network

作者: Yinhan GAO Xilai MA Kaiyu YANG Ruibao WANG

作者单位: Jilin University, China

会议类型: 国际会议

会议名称: 2nd IEEE Conference on Industrial Electronics and Applications(ICIEA 2007)(第二届IEEE工业电子与应用国际会议)

会议地点: 哈尔滨

会议语种:英文

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）