Equalization of supervised data trained RBFNN using MSFLA

Abstract

In order to avoid the channel distortion in signal processing recently, RBFNN based equalizers is mentioned. Hit and trail method is the main provocation problem for design of RBFNN Equalizer. Here the initiation is start with use of the population based optimization algorithm trained RBFNN equalizer, such as Shuffled Frog-Leaping Algorithm as well as its modified forms. The observation is made on the basis of its performance as compared to the other equalizers.