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