Cochannel Interference Minimization Using Wilcoxon Multilayer Perceptron Neural Network

This paper presents the application of wilcoxon machines learning technique for artificial neural network in channel equalization application. The equalizer mitigates the effect of co-channel interference, inter-symbol interference in the presence of additive white Gaussian noise (AWGN). The performance of this proposed Multilayer Perceptron Network equalizer trained with wilcoxon learning has been compared with Linear equalizer trained with recursive-least-squares algorithm and MLP equalizer with back-propagation algorithm. The Performance shows superiority of Wilcoxon Learning Multilayer Perceptron Network equalizer over back-propagation Multilayer Perceptron Network equalizer.