Modified Particle Swarm Optimization for Blind Deconvolution and Identification of Multichannel FIR Filters
| Autor: | Vahid Tabataba Vakili, Vahid Khanagha, Ali Khanagha |
|---|---|
| Přispěvatelé: | BMC, Ed., Geometry and Statistics in acquisition data (GeoStat), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria) |
| Jazyk: | angličtina |
| Rok vydání: | 2010 |
| Předmět: |
Blind deconvolution
Mathematical optimization Finite impulse response Computer science MIMO lcsh:Electronics Computer Science::Neural and Evolutionary Computation Particle swarm optimization lcsh:TK7800-8360 Filter (signal processing) [INFO] Computer Science [cs] Blind identification lcsh:Telecommunication [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Robustness (computer science) Hardware and Architecture Particle Swarm Optimization lcsh:TK5101-6720 Signal Processing MIMO FIR Channel Electrical and Electronic Engineering Algorithm [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing |
| Zdroj: | EURASIP Journal on Advances in Signal Processing EURASIP Journal on Advances in Signal Processing, 2010, Volume 2010, ⟨10.1155/2010/716862⟩ EURASIP Journal on Advances in Signal Processing, Vol 2010 (2010) EURASIP Journal on Advances in Signal Processing, Vol 2010, Iss 1, p 716862 (2010) |
| ISSN: | 1687-6172 1687-6180 |
| DOI: | 10.1155/2010/716862⟩ |
| Popis: | International audience; Blind identification of MIMO FIR systems has widely received attentions in various fields of wireless data communications. Here, we use Particle Swarm Optimization (PSO) as the update mechanism of the well-known inverse filtering approach and we show its good performance compared to original method. Specially, the proposed method is shown to be more robust against lower SNR scenarios or in cases with smaller lengths of available data records. Also, a modified version of PSO is presented which further improves the robustness and preciseness of PSO algorithm. However the most important promise of the modified version is its drastically faster convergence compared to standard implementation of PSO. |
| Databáze: | OpenAIRE |
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