Selective Partial Update Adaptive Filtering Algorithms for Block-Sparse System Identification
نویسندگان
چکیده
The block-sparse normalized least mean square (BS-NLMS) algorithm which takes advantage of sparsity, successfully shows fast convergence in adaptive system identification, control, and other industrial informatics applications. It is also attractive acoustic processing where long impulse response, highly correlated sparse echo path are encountered. However, the major drawback BS-NLMS largely computational complexity. This paper proposes a novel selective partial-update (SPU-BS-NLMS) algorithm. Compared with conventional for proposed elective NLMS blocks scheme determined by smallest squared Euclidean-norm at each iteration instead entire block coefficients to save computations. Computational complexity analysis conducted help researchers select appropriate parameters practical realizations Computer simulations on cancellation verify results effectiveness
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ژورنال
عنوان ژورنال: Security and Communication Networks
سال: 2022
ISSN: ['1939-0122', '1939-0114']
DOI: https://doi.org/10.1155/2022/2207115