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Affine Combination of Diffusion Strategies over Networks
- Publication Year :
- 2020
-
Abstract
- 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.<br />Comment: 31 pages
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2002.03209
- Document Type :
- Working Paper