Distributed Adaptive Filtering of α-Stable Signals

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openAccess

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Journal Title

Journal ISSN

Volume Title

A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Date

2018-10

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Mcode

Degree programme

Language

en

Pages

5
1450 - 1454

Series

IEEE Signal Processing Letters, Volume 25, issue 10

Abstract

A cost-effective framework for distributed filtering of α-stable signals over sensor networks is proposed. To this end, the problem of filtering 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 multi-agent networks is derived. The derived algorithm not only gives an approximation of the formulated optimal solution, but is also cost-effective and scalable with the size of the network. Moreover, performance of the derived algorithm is analyzed and convergence conditions are established.

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Keywords

α-stable random signals, consensus fusion, distributed adaptive filtering, fractional differential, Sensor networks

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Citation

Talebi, S P, Werner, S & Mandic, D 2018, ' Distributed Adaptive Filtering of α-Stable Signals ', IEEE Signal Processing Letters, vol. 25, no. 10, pp. 1450 - 1454 . https://doi.org/10.1109/LSP.2018.2862639