Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009 · 13 citations · 2 references
EngineeringComputer ScienceElectrical EngineeringProbability TheoryStochastic ProcessesUncertainty QuantificationBayesian InferenceBayesian StatisticsDigital Signal ProcessingMarkov ProcessesSignal Detection TheorySignal ProcessingBayesian Signal InferenceSignalsStatistical Signal ModelingStatistical Signal Processing
In many cases one can faced with situation of unknown and unstable statistical models of signals and interferences. It is known that markovian processes give good chance for simulation of random processes with non-Gaussian distribution. In this paper the basic approaches to synthesis of signal detection algorithms are considered under the conditions of parametrical aprioristic uncertainty of both signal and interference situations.
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