The problem of nonlinear filter design using Neural Network (NN) training methods has recently attracted the attention of a growing number of researchers. This paper aims to shortly review and unify the problem setting in which various training NN methods were used to desig optimal Weighted Order Statistics filters and to compare the performance obtained with each method.
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