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    SQUARE-ROOT FORM BASED DERIVATION OF A NOVEL NLMS-LIKE ADAPTIVE FILTERING ALGORITHM

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    In this paper we derive a new adaptive filtering algorithm. Starting from a general square-root formulation [1], we introduce a normalization transform to the updating scheme of the block-diagonal adaptive algorithm presented in [1]. This algorithm is efficiently implemented with a low complexity, the resulting algorithm is similar to the NLMS one. Simulations, in the context of multichannel adaptive filtering with highly intercorrelated channels, show a fast convergence of our new algorithm. 1
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