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Article Dans Une Revue IEEE Transactions on Signal Processing Année : 2020

Affine Combination of Diffusion Strategies over Networks

Résumé

Diffusion adaptation is a powerful strategy for distributed estimation and learning over networks. Motivated by the concept of combining adaptive filters, this work proposes a combination framework that aggregates the operation of multiple diffusion strategies for enhanced performance. By assigning a combination coefficient to each node, and using an adaptation mechanism to minimize the network error, we obtain a combined diffusion strategy that benefits from the best characteristics of all component strategies simultaneously in terms of excess-mean-square error (EMSE). Analyses of the universality are provided to show the superior performance of affine combination scheme and to characterize its behavior in the mean and mean-square sense. Simulation results are presented to demonstrate the effectiveness of the proposed strategies, as well as the accuracy of theoretical findings.
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Dates et versions

hal-03347190 , version 1 (17-09-2021)

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Danqi Jin, Jie Chen, Cédric Richard, Jingdong Chen, Ali H Sayed. Affine Combination of Diffusion Strategies over Networks. IEEE Transactions on Signal Processing, 2020, 68, pp.2087-2104. ⟨10.1109/TSP.2020.2975346⟩. ⟨hal-03347190⟩
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