Name
Abstract | ||
|---|---|---|
We present a fast robust recursive least-squares (FRRLS) algorithm based on a recently introduced new framework for designing robust adaptive filters. The algorithm is the result of minimizing a cost function subject to a time-dependent constraint on the norm of the filter update. Although the characteristics of the exact solution to this problem are known, there is no closed-form solution in general. However, the approximate solution we propose is very close to the optimal one. We also present some theoretical results regarding the asymptotic behavior of the algorithm. The FRRLS is then tested in different environments for system identification and acoustic echo cancellation applications. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/TSP.2008.2010643 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
robust adaptive filter,asymptotic behavior,exact solution,closed-form solution,approximate solution,filter update,different environment,robust recursive least-squares algorithm,fast robust recursive least-squares,cost function subject,acoustic echo cancellation application,robustness,system testing,cost function,closed form solution,impulse noise,adaptive filters,algorithm design and analysis,system identification,adaptive filter | Least squares,Mathematical optimization,Recursion (computer science),Algorithm design,Control theory,Algorithm,Robustness (computer science),Adaptive filter,System identification,Robust control,Recursive least squares filter,Mathematics | Journal |
Volume | Issue | ISSN |
57 | 3 | 1053-587X |
Citations | PageRank | References |
10 | 1.05 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Leonardo Rey Vega | 1 | 107 | 17.14 |
| H. Rey | 2 | 274 | 18.90 |
| Jacob Benesty | 3 | 1386 | 136.42 |
| S. Tressens | 4 | 269 | 18.38 |