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Titlebook: Methods of Signal Processing for Adaptive Antenna Arrays; Larysa Titarenko,Alexander Barkalov Book 2013 Springer-Verlag Berlin Heidelberg

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Synthesis of ASF Algorithms for Not Exactly Known Parameters,hods. The proposed algorithms are resistant to the value of input signal/noise relation for the wide class of signal-interference environments. They provide the values of output signal/(interference + noise) relation practically equal to the potentially reachable.
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General Characteristic of Methods for STSP,gnal processing is analysed. The beginning of the chapter discusses the main methods of nonadaptive spatial signal processing. Next, the peculiarities of adaptive spatial signal processing are analysed. The third part of the chapter is devoted to non-structural methods of adaptive space-time signal
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Background of Classical Theory of ASSP,e situation. Next, the criteria of optimality are analysed. The definition of a system of criteria of optimality is given. In the last part of the chapter there is an analysis of algorithms oriented on adaptive space-time signal processing.
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Algorithms of ASSP with Not Exactly Known Parameters,development of effective algorithms of adaptive spatial signal processing with not exactly known parameters. The probabilistic approach for synthesis of robust algorithms of ASSP is analysed. Next, the deterministic approach for synthesis of robust algorithms of ASSP is represented as a solution of
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Background of ASSP with Not Exactly Known Parameters, elements of axiomatic and some analogues as well as elements of the theory of generalized linear systems are introduced. It is shown that the problem of development of effective algorithms of adaptive spatial signal processing with not exactly known parameters is reduced to construction of some ope
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Synthesis of ASF Algorithms for Not Exactly Known Parameters,th signals and interferences. The methods are implemented as both determinate and stochastic recurrent procedures . The recurrent algorithms are proposed using adaptive operators including constructing optimization tasks with either square or mixed constraints. The proposed approach is based on repl
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