| Full text | |
| Author(s): |
Fernandez-Bes, Jesus
[1]
;
Azpicueta-Ruiz, Luis A.
[1]
;
Arenas-Garcia, Jeronimo
[1]
;
Silva, Magno T. M.
[2]
Total Authors: 4
|
| Affiliation: | [1] Univ Carlos III Madrid, Dept Signal Theory & Commun, Leganes 28911 - Spain
[2] Univ Sao Paulo, Escola Politecn, Dept Elect Syst Engn, BR-05508010 Sao Paulo - Brazil
Total Affiliations: 2
|
| Document type: | Journal article |
| Source: | DIGITAL SIGNAL PROCESSING; v. 36, p. 1-14, JAN 2015. |
| Web of Science Citations: | 11 |
| Abstract | |
We propose a diffusion scheme for adaptive networks, where each node obtains an estimate of a common unknown parameter vector by combining a local estimate with the combined estimates received from neighboring nodes. The combination weights are adapted in order to minimize the mean-square error of the network employing a local least-squares (LS) cost function. This adaptive diffusion network with LS combiners (ADN-LS) is analyzed, deriving expressions for its network mean-square deviation that characterize the convergence and steady-state performance of the algorithm. Experiments carried out in stationary and tracking scenarios show that our proposal outperforms a state-of-art scheme for adapting the weights of diffusion networks (ACW algorithm from {[}10], both during convergence and in tracking situations. Despite its good convergence behavior, our proposal may present a slightly worse steady-state performance in stationary or slowly-changing scenarios with respect to ACW due to the error inherent to the least-squares adaptation with sliding window. Therefore, to take advantage of these different behaviors, we also propose a hybrid scheme based on a convex combination of the ADN-LS and ACW algorithms. (C) 2014 Elsevier Inc. All rights reserved. (AU) | |
| FAPESP's process: | 12/24835-1 - Adaptive algorithms, combinations and applications in deconvolution |
| Grantee: | Magno Teófilo Madeira da Silva |
| Support type: | Regular Research Grants |
| FAPESP's process: | 13/18041-5 - Combination of adaptive algorithms and distributed adaptive filtering applied to acoustics |
| Grantee: | Magno Teófilo Madeira da Silva |
| Support type: | Research Grants - Visiting Researcher Grant - International |