Name
Abstract | ||
|---|---|---|
Recently, the proportionate normalized least mean square (PNLMS) algorithm was developed for use in network echo cancelers. In comparison to the normalized least mean square (NLMS) algorithm, PNLMS has very fast initial convergence and tracking when the echo path is sparse. Unfortunately, when the impulse response is dispersive, the PNLMS converges much slower than NLMS. This implies that the rule proposed in PNLMS is far from optimal. In many simulations, it seems that we fully benefit from PNLMS only when the impulse response is close to a delta function. In this paper, we propose a new rule that is more reliable than the one used in PNLMS. Many simulations show that the new algorithm (improved PNLMS) performs better than NLMS and PNLMS, whatever the nature of the impulse response is. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/ICASSP.2002.5744994 | ICASSP), 2002 IEEE International Conference |
Keywords | Field | DocType |
artificial intelligence,detectors,dispersion,least squares approximation,impulse response | Convergence (routing),Least mean squares filter,Least squares,Transient response,Impulse response,Mathematical optimization,Control theory,Computer science,Algorithm,Adaptive filter,Normalized least mean square algorithm,Filtering theory | Conference |
Volume | ISSN | ISBN |
2 | 1520-6149 | 0-7803-7402-9 |
Citations | PageRank | References |
80 | 5.71 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jacob Benesty | 1 | 1941 | 146.01 |
| S. L. Gay | 2 | 129 | 18.00 |