A class of diffusion proportionate subband adaptive filters for sparse system identification over distributed networks

Pouradabi, A., Rastegarnia, A., Zandi, S., Bazzi, W.M. and Sanei, S. ORCID: 0000-0002-3437-2801, 2021. A class of diffusion proportionate subband adaptive filters for sparse system identification over distributed networks. Circuits, Systems, and Signal Processing. ISSN 0278-081X

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Abstract

This paper aims to extend the proportionate adaptation concept to the design of a class of diffusion normalized subband adaptive filter (DNSAF) algorithms. This leads to four extensions of the algorithm associated with different step-size variations, namely diffusion proportionate normalized subband adaptive filter (DPNSAF), diffusion μ-law PNSAF (DMPNSAF), diffusion improved PNSAF (DIPNSAF) and diffusion improved IPNSAF (DIIPNSAF). Subsequently, steady-state performance, stability conditions and computational complexity of the proposed algorithms are investigated. For each extension the performance has been evaluated using both real and simulated data, where the outcomes demonstrate the accuracy of the theoretical expressions and effectiveness of the proposed algorithms.

Item Type: Journal article
Publication Title: Circuits, Systems, and Signal Processing
Creators: Pouradabi, A., Rastegarnia, A., Zandi, S., Bazzi, W.M. and Sanei, S.
Publisher: Springer Science and Business Media LLC
Date: 17 June 2021
ISSN: 0278-081X
Identifiers:
NumberType
10.1007/s00034-021-01766-xDOI
1464387Other
Divisions: Schools > School of Science and Technology
Record created by: Laura Ward
Date Added: 31 Aug 2021 09:39
Last Modified: 31 Aug 2021 09:39
URI: http://irep.ntu.ac.uk/id/eprint/44092

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