Name
Abstract | ||
|---|---|---|
The LMS algorithm suffers from its slow rate of convergence, especially for high correlated input signal. The input pre-whitening based algorithms provide better convergence rate with the price of noise enhancement. To mitigate this drawback, we present in this paper a technique, which consists on exciting the adaptive filter at both the input signal direction and the pre-whitened input direction. Hence, two different step sizes are used, they permit to improve convergence rate without enhancing the noise during steady state. A theoretical analysis of the steady state performance is presented. Simulation results are also presented to support the analysis and to compare the proposed algorithm with classical ones. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICASSP.2006.1660603 | 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, Vols 1-13 |
Keywords | Field | DocType |
rate of convergence,convergence rate,adaptive filter,convergence,adaptive filters,least squares approximation,noise reduction,computational modeling,algorithm design and analysis,steady state,decorrelation,lms algorithm | Least mean squares filter,Noise reduction,Convergence (routing),Mathematical optimization,Algorithm design,Decorrelation,Control theory,Computer science,Algorithm,Rate of convergence,Adaptive filter,Steady state | Conference |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
3 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hichem Besbes | 1 | 80 | 22.41 |
| Sofia Ben Jebara | 2 | 26 | 10.15 |