Distributed Adaptive Filtering of α-Stable Signals

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Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Date
2018-10
Major/Subject
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.
Description
Käsikirjoitus avataan, kun artikkeli julkaistu.
Keywords
α-stable random signals, consensus fusion, distributed adaptive filtering, fractional differential, Sensor networks
Other note
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