A PSO based Functional Link Artificial Neural Network training algorithm for equalization of digital communication channels

Author

Yogi, Sandhya ; Subhashini, K.R. ; Satapathy, J.K.

Author_Institution

Dept. of Electr. Eng., NIT, Rourkela, India

fYear

2010

fDate

July 29 2010-Aug. 1 2010

Firstpage

107

Lastpage

112

Abstract

This paper presents a new approach to equalization of communication channels using Functional Link Artificial Neural Networks (FLANNs). A novel method of training the FLANNs using PSO Algorithm is described. The performance of the proposed network has been compared with the conventional LMS based channel equalizer and FLANN trained with BP algorithm based equalizer. From the results it can be noted that the proposed algorithm improves the classification capability of the FLANNs in differentiating the received data.

Keywords

backpropagation; channel estimation; digital communication; neural nets; particle swarm optimisation; BP algorithm; FLANN classification; PSO based functional link artificial neural network training algorithm; digital communication channel equalization; particle swarm optimisation; Artificial neural networks; Bit error rate; Convergence; Digital communication; Equalizers; Least squares approximation; Signal to noise ratio; Adaptive Channel Equalization; Artificial Neural Networks; Fitness function; Global best value; PSO;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial and Information Systems (ICIIS), 2010 International Conference on

Conference_Location

Mangalore

Print_ISBN

978-1-4244-6651-1

Type

conf

DOI

10.1109/ICIINFS.2010.5578726

Filename

5578726