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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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1464387_Sanei.pdf - Post-print Download (2MB) | Preview |
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 | ||||||
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| 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 | ||||||
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| Divisions: | Schools > School of Science and Technology | ||||||
| Record created by: | Laura Ward | ||||||
| Date Added: | 31 Aug 2021 09:39 | ||||||
| Last Modified: | 17 Jun 2022 03:00 | ||||||
| URI: | https://irep.ntu.ac.uk/id/eprint/44092 |
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