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Decomposition of random field's processing

In this paper we consider a technique for achieving fast computing and fast convergence multichannel digital signal processing based on reducing the dimension of processing space. Parallel decomposition of the multidimensional processing to basic transforms is proposed. Applying this decomposition for Wiener's filtering gives us the possibility to build efficient parallel computing structures. Applications of these results include high dimensional real-time image and signal processing, filtering, and so on.