Distributed adaptive filtering of alpha-stable signals
Journal article, Peer reviewed
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Original versionIEEE Signal Processing Letters. 2018, 25 (10), 1450-1454. 10.1109/LSP.2018.2862639
A cost-effective framework for distributed adaptive filtering of α-stable signals over sensor networks is proposed. First, the filtering paradigm of α-stable signals through multiple observations made over a network of sensors is revisited and an optimal solution is formulated. Then, an adaptive gradient descent based algorithm for distributed real-time filtering of α-stable signals via multiagent networks is derived. This not only provides an approximation of the formulated optimal solution, but also a cost-effective algorithm that scales with the size of the network. Moreover, performance of the derived algorithm is analyzed and convergence conditions are established.