1. Normalized Least Mean M-Estimate Algorithm with Switching Step-Sizes Against Impulsive Noises.
- Author
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Guo, Peng, Yu, Yi, He, Hongsen, Li, Ke, and Yu, Tao
- Subjects
- *
ALGORITHMS , *NOISE , *CARRIER transmission on electric lines - Abstract
The normalized least mean M-estimate (NLMM) algorithm exhibits good robustness in impulsive noises, but it suffers from the trade-off between convergence rate and steady-state misadjustment. In response to this problem, this paper proposes a switching step-sizes NLMM (SSS-NLMM) algorithm, which selects the optimal step-size at each iteration by comparing the mean square deviation (MSD) values of the algorithm with different step-sizes. Furthermore, to improve the convergence of the algorithm in the transition stage, we embed a feedback mechanism on the minimum MSD. Simulations in various environments have verified that the proposed SSS-NLMM algorithm has better performance than its counterparts in terms of convergence rate and steady-state misadjustment. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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