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Robust Distributed Diffusion Recursive Least Squares Algorithms With Side Information for Adaptive Networks.
- Source :
- IEEE Transactions on Signal Processing; 3/15/2019, Vol. 67 Issue 6, p1566-1581, 16p
- Publication Year :
- 2019
-
Abstract
- This work develops robust diffusion recursive least-squares algorithms to mitigate the performance degradation often experienced in networks of agents in the presence of impulsive noise. The first algorithm minimizes an exponentially weighted least-squares cost function subject to a time-dependent constraint on the squared norm of the intermediate update at each node. A recursive strategy for computing the constraint is proposed using side information from the neighboring nodes to further improve the robustness. We also analyze the mean-square convergence behavior of the proposed algorithm. The second proposed algorithm is a modification of the first one based on the dichotomous coordinate descent iterations. It has a performance similar to that of the former, however, its complexity is significantly lower especially when input regressors of agents have a shift structure and it is well suited to practical implementation. Simulations show the superiority of the proposed algorithms over previously reported techniques in various impulsive noise scenarios. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1053587X
- Volume :
- 67
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Signal Processing
- Publication Type :
- Academic Journal
- Accession number :
- 134552053
- Full Text :
- https://doi.org/10.1109/TSP.2019.2893846