Abstract
ABSTRACTIn this paper we consider technique for achieving fast computing and fast convergence multichannel digital signal processing based on reducing the dimension of processing space. Parallel decomposition the multidimensional processing to basic transforms is proposed. Applying this decomposition for Wiener's filtering gives possibility to build efficientparallel computing structures. Applications of these results include high dimensional real-time image and signal processing, filtering and so on. 2. MATHEMATICAL THEORY OF DECOMPOSITION Theory of least-square filtering of random processes and fields was based on classic works of N.Wiener1, T.Kailath2 and others. We discuss family of some useful transformations of multidimensional signal. It is extension of well-known lattice technique of signal processing3, but give some new formalism to work with.Let's array of N sensors -linear array, Let's output of array of sensors is x(t) =s(t)+n (1), t=1, 2,3,... (1)
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