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To improve the performance for identifying the block sparse system, a block sparse reweighted zero-attracting normalised least mean square algorithm (NLMS) (BS-RZA-NLMS) is proposed in this Letter. The proposed algorithm is derived by applying block sparsity constraint on the cost function of the NLMS, which is a log-sum penalty of adaptive tap weights with equal block partition sizes. The convergence...
By minimising a new cost function that contains robust set-membership error bound, a bias-compensated robust set-membership normalised least mean square (NLMS) algorithm is proposed, which is characterised by its robustness against impulsive noises and noisy inputs. To estimate the input noise variance in impulsive noise environments, a new estimation method is proposed in which there is no need to...
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