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Adaptive step size independent vector analysis for blind source separation

Liang, Y, Naqvi, SM and Chambers, JA (2011) Adaptive step size independent vector analysis for blind source separation

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Abstract

In this paper, a novel adaptive step size independent vector analysis (ASS-IVA) method is proposed for blind source separation. Independent vector analysis (IVA) can successfully solve the classical permutation problem in the blind source separation (BSS) field. In the ASS-IVA method the step size is adjusted during learning to enhance the convergence behavior of the conventional IVA algorithm. The experimental results confirm that the proposed method improves the convergence speed greatly as compared to the original IVA method, whilst retaining the excellent separation properties of the IVA method. © 2011 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
NameEmailORCID
Liang, YUNSPECIFIEDUNSPECIFIED
Naqvi, SMUNSPECIFIEDUNSPECIFIED
Chambers, JAj.a.chambers@surrey.ac.ukUNSPECIFIED
Date : 29 September 2011
Identification Number : https://doi.org/10.1109/ICDSP.2011.6004870
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 13:24
Last Modified : 17 May 2017 13:24
URI: http://epubs.surrey.ac.uk/id/eprint/839124

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