Recognition of non-Gaussian signals against a background of noise using higher order statistics

The aim of the paper is to study the possibility of advancing noised non-Gaussian processes recognition using the features based on higher-order statistics. Several new recognition features based on the higher-order statistics, the basis of advancing recognition results in the presence of noise, decision rules and recognition system frameworks we proposed in the paper. The efficiency test of the proposed method is performed by statistical modeling. We proposed features of recognition based on the third-order statistics.