DocumentCode :
390012
Title :
Wavelet neural networks for adaptive equalization
Author :
Jiang, Minghu ; Gielen, Georges ; Deng, Beixing ; Tang, Xiaofang ; Ruan, Qiuqi ; Yuan, Baozong
Author_Institution :
Dept. of Electr. Eng, Katholieke Univ., Leuven, Heverlee, Belgium
Volume :
2
fYear :
2002
fDate :
26-30 Aug. 2002
Firstpage :
1251
Abstract :
A structure based on the wavelet neural networks is proposed for nonlinear channel equalization in a digital communication system, the minimum error probability (MEP) is applied as performance criterion to update the weighting matrix of wavelet networks. Our experimental results show that performance of the proposed wavelet networks based on equalizer can significantly improve the neural modeling accuracy and outperform the conventional neural networks in signal to noise ratio and channel non-linearity.
Keywords :
adaptive equalisers; digital communication; error statistics; learning (artificial intelligence); matrix algebra; neural nets; wavelet transforms; SNR; adaptive equalization; channel nonlinearity; digital communication system; learning algorithm; minimum error probability; neural modeling accuracy; nonlinear channel equalization; nonlinear distortion compensation; performance criterion; signal to noise ratio; wavelet neural networks; weighting matrix updating; Adaptive equalizers; Adaptive systems; Bit error rate; Digital communication; Error probability; Feature extraction; Multi-layer neural network; Neural networks; Signal processing; Wavelet domain;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, 2002 6th International Conference on
Print_ISBN :
0-7803-7488-6
Type :
conf
DOI :
10.1109/ICOSP.2002.1180018
Filename :
1180018
Link To Document :
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