Nonlinear channel equalization with maximum covariance initialized cascade-correlation learning

In this paper we have studied maximum covariance initialization scheme and cascade-correlation learning to improve the performance of a multilayer perceptron network equalizer in nonlinear channel environment. The initialization scheme enables faster convergence and the cascade-correlation learning provides adaptive network size. These methods are compared to a traditional MLP network equalizer and to a simple linear equalizer.