Polynomial Algorithms for Detecting Signals in the Background correlated non-Gaussian interference
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Abstract
The development of method testing statistical hypotheses for a synthesis and analysis of nonlinear algorithms of signals detection on a background Non-Gaussian noise is considered. The new method based of the use of polynomial decision rules and momentcumulant description of random variable. It is show that the use of joint moments of different orders is given possibility to take into account cross-correlation properties of random variable and their Non-Gaussian distributing. The got results show that nonlinear processing of selective values and account of structure of Non-Gaussian noise as coefficients of asymmetry and excess allows increasing of efficiency of decision rules.
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