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LMS algorithm with gradient descent filter length

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3 Author(s)
Yuantao Gu ; Dept. of Electron. Eng., Tsinghua Univ., Beijing, China ; Kun Tang ; Huijuan Cui

This letter presents a novel variable-length least mean square algorithm, whose filter length is adjusted dynamically along the negative gradient direction of the squared estimation error. Compared with other variable-length algorithms, the proposed algorithm has faster convergence and more robust performance in diverse environments.

Published in:

Signal Processing Letters, IEEE  (Volume:11 ,  Issue: 3 )