DocumentCode :
3449152
Title :
The Research on Identification for Electromagnetic Interference in Automobile Based on WPD and MLPNN
Author :
Gao, Yinhan ; Ma, Xilai ; Yang, Kaiyu ; Wang, Ruibao
Author_Institution :
Jilin Univ. Changchun, Changchun
fYear :
2007
fDate :
23-25 May 2007
Firstpage :
2350
Lastpage :
2353
Abstract :
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 Parseval´s 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.
Keywords :
automobiles; electromagnetic interference; multilayer perceptrons; signal processing; wavelet transforms; EM-Test; Parseval´s theorem energy rule; automobile; electromagnetic interference; feature extraction; interferences identification; multilayer perceptron neural network; signal identification; signal recognition; wavelet packet decomposition; Automobiles; Electromagnetic interference; Industrial electronics; electromagnetic compatibility; multilayer perceptron; neural network; wavelet packet decomposition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-0737-8
Electronic_ISBN :
978-1-4244-0737-8
Type :
conf
DOI :
10.1109/ICIEA.2007.4318830
Filename :
4318830
Link To Document :
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