Skip to Main content Skip to Navigation
Journal articles

Modified Particle Swarm Optimization for Blind Deconvolution and Identification of Multichannel FIR Filters

Abstract : 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.
Complete list of metadatas

https://hal.inria.fr/inria-00479523
Contributor : Vahid Khanagha <>
Submitted on : Friday, April 30, 2010 - 7:03:41 PM
Last modification on : Friday, April 12, 2019 - 11:14:05 AM
Document(s) archivé(s) le : Thursday, September 30, 2010 - 4:52:44 PM

File

vahid_hindawi.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Vahid Khanagha, Ali Khanagha, Vahid Tabataba Vakili. Modified Particle Swarm Optimization for Blind Deconvolution and Identification of Multichannel FIR Filters. EURASIP Journal on Advances in Signal Processing, SpringerOpen, 2010, Volume 2010, ⟨10.1155/2010/716862⟩. ⟨inria-00479523⟩

Share

Metrics

Record views

330

Files downloads

408