Name
Abstract | ||
|---|---|---|
In the presence of impulsive noises, the normalized least mean M-estimate (NLMM) algorithm has behaved better robustness and convergence than the normalized least mean square (NLMS) algorithm. In order to further solve the trade-off of the NLMM algorithm between convergence rate and steady-state misadjustment, we design a combined step-size (CSS) scheme that combines large and small step-sizes through an adaptive mixing factor, and the resulting CSS-NLMM algorithm obtains fast convergence and low steady-state misadjustment simultaneously. Importantly, the proposed CSS scheme can be straightforwardly extended to other robust NLMS algorithms. Moreover, the performance analysis of the CSS-NLMM algorithm is provided. Simulation results in impulsive noises have supported the effectiveness of the proposed CSS-NLMM algorithm and its performance analysis. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.dsp.2022.103609 | Digital Signal Processing |
Keywords | DocType | Volume |
Combined step-size,Impulsive noises,M-estimate,Robust NLMS algorithms | Journal | 128 |
ISSN | Citations | PageRank |
1051-2004 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peng Guo | 1 | 0 | 0.34 |
| y yu | 2 | 3 | 5.12 |
| Tao Yang | 3 | 160 | 76.32 |
| Hongsen He | 4 | 0 | 0.34 |
| Rodrigo C. de Lamare | 5 | 1461 | 179.59 |