Journal
IEEE TRANSACTIONS ON SIGNAL PROCESSING
Volume 58, Issue 9, Pages 4795-4810Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2010.2051429
Keywords
Adaptive filter; adaptive networks; combination; diffusion; distributed algorithm; distributed estimation; energy conservation
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Funding
- National Science Foundation [ECS-0601266, ECS-0725441, CCF-0942936]
- Japan Society for the Promotion of Science (JSPS)
- Direct For Computer & Info Scie & Enginr [0942936] Funding Source: National Science Foundation
- Division of Computing and Communication Foundations [0942936] Funding Source: National Science Foundation
- Division of Computing and Communication Foundations
- Direct For Computer & Info Scie & Enginr [GRANTS:13677290] Funding Source: National Science Foundation
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This paper presents an efficient adaptive combination strategy for the distributed estimation problem over diffusion networks in order to improve robustness against the spatial variation of signal and noise statistics over the network. The concept of minimum variance unbiased estimation is used to derive the proposed adaptive combiner in a systematic way. The mean, mean-square, and steady-state performance analyses of the diffusion least-mean squares (LMS) algorithms with adaptive combiners are included and the stability of convex combination rules is proved. Simulation results show i) that the diffusion LMS algorithm with the proposed adaptive combiners outperforms those with existing static combiners and the incremental LMS algorithm, and ii) that the theoretical analysis provides a good approximation of practical performance.
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