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Khalili, A., Rastegarnia, A., Farzamnia, A., Sanei, S. 
ORCID: 0000-0002-3437-2801 and Alghamdi, T.A.H.,
2024.
Tracking analysis of maximum Versoria criterion based adaptive filter.
IEEE Access, 12, pp. 30747-30753.
ISSN 2169-3536
Abstract
Recently, maximum Versoria criterion-based adaptive algorithms have been introduced as a new solution for robust adaptive filtering. This paper studies the steady-state tracking analysis of an adaptive filter with maximum Versoria criterion (MVC) in a non-stationary (Markov time-varying) system. Our analysis relies on the energy conservation method. Both Gaussian and general non-Gaussian noise are considered, and for both cases, the closed-form expression for steady-state excess mean square error (EMSE) is derived. Regardless of noise type, unlike the stationary environment, the EMSE curves are not increasing functions of step-size parameter. The validity of the theoretical results is justified via simulation.
| Item Type: | Journal article | ||||||
|---|---|---|---|---|---|---|---|
| Publication Title: | IEEE Access | ||||||
| Creators: | Khalili, A., Rastegarnia, A., Farzamnia, A., Sanei, S. and Alghamdi, T.A.H. | ||||||
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) | ||||||
| Date: | 26 February 2024 | ||||||
| Volume: | 12 | ||||||
| ISSN: | 2169-3536 | ||||||
| Identifiers: |
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| Rights: | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/ | ||||||
| Divisions: | Schools > School of Science and Technology | ||||||
| Record created by: | Jeremy Silvester | ||||||
| Date Added: | 24 May 2024 08:55 | ||||||
| Last Modified: | 24 May 2024 08:55 | ||||||
| URI: | https://irep.ntu.ac.uk/id/eprint/51472 |
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