Welcome to the InfoSci Platform
Reference Hub5
Multilayer Perceptron Based Equalizer with an Improved Back Propagation Algorithm for Nonlinear Channels

Multilayer Perceptron Based Equalizer with an Improved Back Propagation Algorithm for Nonlinear Channels

Zohra Zerdoumi, Djamel Chikouche, Djamel Benatia
Copyright: © 2016 |Volume: 7 |Issue: 3 |Pages: 16
ISSN: 1937-9412|EISSN: 1937-9404|EISBN13: 9781466689923|DOI: 10.4018/IJMCMC.2016070102
Cite Article Cite Article

MLA

Zerdoumi, Zohra, et al. "Multilayer Perceptron Based Equalizer with an Improved Back Propagation Algorithm for Nonlinear Channels." IJMCMC vol.7, no.3 2016: pp.16-31. http://doi.org/10.4018/IJMCMC.2016070102

APA

Zerdoumi, Z., Chikouche, D., & Benatia, D. (2016). Multilayer Perceptron Based Equalizer with an Improved Back Propagation Algorithm for Nonlinear Channels. International Journal of Mobile Computing and Multimedia Communications (IJMCMC), 7(3), 16-31. http://doi.org/10.4018/IJMCMC.2016070102

Chicago

Zerdoumi, Zohra, Djamel Chikouche, and Djamel Benatia. "Multilayer Perceptron Based Equalizer with an Improved Back Propagation Algorithm for Nonlinear Channels," International Journal of Mobile Computing and Multimedia Communications (IJMCMC) 7, no.3: 16-31. http://doi.org/10.4018/IJMCMC.2016070102

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Neural network based equalizers can easily compensate channel impairments; such additive noise and inter symbol interference (ISI). The authors present a new approach to improve the training efficiency of the multilayer perceptron (MLP) based equalizer. Their improvement consists on modifying the back propagation (BP) algorithm, by adapting the activation function in addition to the other parameters of the MLP structure. The authors report on experiment results evaluating the performance of the proposed approach namely the back propagation with adaptive activation function (BPAAF) next to the BP algorithm. To further prove its effectiveness, the proposed approach is also compared beside a so known nonlinear equalizer explicitly the multilayer perceptron with decision feedback equalizer MLPDFE. The authors consider various performance measures specifically: signal resorted quality, lower steady state MSE reached and minimum bit error rate (BER) achieved, where nonlinear channel equalization problems are employed.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.