Distributed Adaptive Filtering of α-Stable Signals

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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.

Original languageEnglish
Pages (from-to)1450 - 1454
Number of pages5
JournalIEEE Signal Processing Letters
Volume25
Issue number10
DOIs
Publication statusPublished - Oct 2018
MoE publication typeA1 Journal article-refereed

Keywords

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

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