An Improved ZA-LMS Algorithm for Sparse System Identification with Variable Sparsity
2014 ◽
Vol 602-605
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pp. 2415-2419
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The standard least mean square algorithm does not consider the sparsity of the impulse response,and the performs of the ZA-LMS algorithm deteriorates ,as the degree of system sparsity reduces or non-sparse . Concerning this issue ,the ZA-LMS algorithm is studied and modified in this paper to improve the performance of sparse system identification .The improved algorithm by modify the zero attraction term, which attracts the coefficients only in a certain range (the “inactive” taps), thus have a good performance when the sparsity decreases. The simulations demonstrate that the proposed algorithm significantly outperforms then the ZA-LMS with variable sparisity.
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2019 ◽
Vol 33
(11)
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pp. 1695-1705
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