Name
Abstract | ||
|---|---|---|
This paper proposes a new variable step-size LMS (VSLMS) algorithm with an approach in which a gradient-based weighted average of a kurtosis of an estimated error signal is used to improve the drawback of a previous algorithm for application to an unknown channel estimation. The proposed scheme leads not only to the enhancement of the convergence rate, but also to robustness in terms of low-SNR environments. It could also lead to obtaining a lower misadjustment error. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/LSP.2010.2040929 | IEEE Signal Process. Lett. |
Keywords | Field | DocType |
least mean square,least-mean-square (lms),variable step-size,kurtosis,adaptive signal processing,adaptive filters,least mean squares methods,gradient-based variable step-size scheme,estimated error,channel estimation,least squares approximation,convergence rate,signal processing,convergence,cost function,robustness,error correction,adaptive filter,steady state | Convergence (routing),Least mean squares filter,Least squares,Mathematical optimization,Robustness (computer science),Error detection and correction,Adaptive filter,Rate of convergence,Mathematics,Kurtosis | Journal |
Volume | Issue | ISSN |
17 | 4 | 1070-9908 |
Citations | PageRank | References |
5 | 0.48 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jeng-Kuang Hwang | 1 | 71 | 16.18 |
| Yuanping Li | 2 | 48 | 6.10 |