Application of the MLP neural networks for analyzing non Gaussian signal

In this investigation we applied the Multi Layer Perceptron (MLP) neural networks for modeling and predicting a real non Gaussian process. The obtained results show that an agreement between predicted and measured values. The statistical error analysis used to evaluate the performance of the correlations, between measured and predicted values provides satisfactory results. The developed model is tested and compared with an other model based on Volterra system. The obtained result demonstrates the efficiency of the developed model.