Tracking Dynamic Systems in α-Stable Environments

  • Sayed Pouria Taleb
  • , Stefan Werner
  • , Shengxi Li
  • , Danilo P. Mandic

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In order to accommodate for modern adaptive filtering applications, the classic adaptive filtering paradigm is considered from a more general perspective. The new formulation allows for time dependent variations in the state of the system and more importantly it relaxes the Gaussian assumption to the generalized setting of α-stable distributions. In this work, based on the principles of gradient descent and fractional-order calculus, a cost-effective technique for tracking the state of such a system is derived. For rigour, performance of the derived filtering technique is analyzed and convergence conditions are established.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4853-4857
Number of pages5
ISBN (Electronic)9781479981311
DOIs
StatePublished - May 2019
Externally publishedYes
Event44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Brighton, United Kingdom
Duration: 12 May 201917 May 2019

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2019-May
ISSN (Print)1520-6149

Conference

Conference44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
Country/TerritoryUnited Kingdom
CityBrighton
Period12/05/1917/05/19

Keywords

  • adaptive filtering/tracking
  • fractional-order calculus
  • fractional-order filtering
  • α-stable signals

Fingerprint

Dive into the research topics of 'Tracking Dynamic Systems in α-Stable Environments'. Together they form a unique fingerprint.

Cite this