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Sparsity-Aware Adaptive Algorithms Based on Alternating Optimization and Shrinkage
IEEE Signal Processing Letters
This letter proposes a novel sparsity-aware adaptive filtering scheme and algorithms based on an alternating optimization strategy with shrinkage. The proposed scheme employs a twostage structure that consists of an alternating optimization of a diagonally-structured matrix that speeds up the convergence and an adaptive filter with a shrinkage function that forces the coefficients with small magnitudes to zero. We devise alternating optimization least-mean square (LMS) algorithms for thedoi:10.1109/lsp.2014.2298116 fatcat:ecc3bkuygvbjdozlkehg6xpaey