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2018
Conference Paper
Titel
A Hybrid Dictionary Approach for Distributed Kernel Adaptive Filtering in Diffusion Networks
Abstract
We propose a hybrid dictionary approach for distributed kernel-based adaptive learning of a nonlinear function by a network of nodes. The hybrid dictionary incorporates a local part to improve learning of high frequency components in the function within the local domain of each node and a global part to provide a consensus estimate of the function over the whole region of interest. We apply our scheme to the reconstruction of a spatial distribution by a network of mobile nodes. Performance evaluations show that high frequency components are reconstructed accurately by our hybrid dictionary approach while common schemes are not able to recover them completely.