Name
Abstract | ||
|---|---|---|
A variable regularized Affine Projection Algorithm (VR-APA) is introduced, which does not require the classical step size. Its use is supported from different points of view. First, it has the property of being H optimal, providing robust behavior against perturbations and model uncertainties. Second, the time varying regularization parameter is obtained by maximizing the speed of convergence of the algorithm. At each time step, it needs knowledge of the power of the estimation error vector, which can be estimated by averaging observable quantities. Although we first derive it for a linear time invariant (LTI) system, we show that the same expression holds if we consider a time varying system following a first order Markov model. Simulation results are presented to test the performance of the proposed algorithm and to compare it with other schemes under different situations. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICASSP.2006.1660624 | 2006 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-13 |
Keywords | Field | DocType |
linear time invariant,first order,vectors,noise measurement,convergence,adaptive filtering,markov model,markov processes,adaptive filters | Convergence (routing),LTI system theory,Mathematical optimization,Markov process,Observable,Noise measurement,Markov model,Regularization (mathematics),Adaptive filter,Mathematics | Conference |
ISSN | Citations | PageRank |
1520-6149 | 7 | 1.28 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| H. Rey | 1 | 274 | 18.90 |
| Leonardo Rey Vega | 2 | 107 | 17.14 |
| S. Tressens | 3 | 269 | 18.38 |
| Jacob Benesty | 4 | 1941 | 146.01 |