Fast communication: Gradient optimization p-norm-like constraint LMS algorithm for sparse system estimation

Authors:
F. Y. Wu;F. Tong
Affiliations:
Key Laboratory of Underwater Acoustic Communication and Marine Information Technology of the Minister of Education, Xiamen University, Xiamen, Fujian 361005, China;Key Laboratory of Underwater Acoustic Communication and Marine Information Technology of the Minister of Education, Xiamen University, Xiamen, Fujian 361005, China
Venue:
Signal Processing
Year:
2013

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Abstract

In order to improve the sparsity exploitation performance of norm constraint least mean square (LMS) algorithms, a novel adaptive algorithm is proposed by introducing a variable p-norm-like constraint into the cost function of the LMS algorithm, which exerts a zero attraction to the weight updating iterations. The parameter p of the p-norm-like constraint is adjusted iteratively along the negative gradient direction of the cost function. Numerical simulations show that the proposed algorithm has better performance than traditional l"0 and l"1 norm constraint LMS algorithms.