Abstract
This paper considers the problem of signal detection in non-Gaussian noise. We propose the novel moment quality criterion decision making, where the moment's description of a random process is used for synthesis of polynomial decision rules. It is shown that the nonlinear processing of samples and taking into account higher order statistics of random process can increase the efficiency of signal detection. It is shown that the proposed models and methods allow us to increase the efficiency of signal processing in comparison with the known results.
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