МОДЕЛІ ТА МЕТОДИ ВИЯВЛЕННЯ СИГНАЛІВ НА ФОНІ НЕГАУСОВИХ КОРЕЛЬОВАНИХ ЗАВАД

The development of high-quality signal detection systems requires complete information about the type of random processes distributions in communication channels with noise. One of the advanced approaches that allows describe random
variables is the use of moment and cumulant description of random processes. The article proposes a synthesis of new cumulant models and methods of signal detection in additive correlated non-Gaussian noise. For this purpose, stochastic
polynomials of finite degree are used, the optimal coefficients of which are determined according to the adapted new decision-making quality criterion. The nonlinear processing of signals in non-Gaussian noise can increase the signal processing efficiency compared to traditional Gaussian random process models.