New criteria for blind source separation using second-order cyclic statistics
type: Item
instance of: scholarly article
title: New criteria for blind source separation using second-order cyclic statistics
zbMATH Open document ID: 0953.93068
DOI: 10.1007/BF01229991
author: Ying-Chang Liang
author: A. Rahin Leyman
author: Francois Chin
published in: Circuits, Systems, and Signal Processing
publication date: 2001-01-22T00:00:00Z
review text: The paper deals with the problem of blind separation of cyclo-stationary sources. The authors propose two algorithms for blind source separation which are based on second-order cyclic statistics. Both methods do not need any restrictions on the distributions of the signals. They are applicable to any stationary correlated or uncorrelated Gaussian or non-Gaussian noises. The effectiveness of the proposed approach is illustrated by a simulation example.
reviewed by: Bernd Mathiszik
Mathematics Subject Classification ID: 93E11
Mathematics Subject Classification ID: 94A12
Mathematics Subject Classification ID: 93E35
zbMATH DE Number: 1422957
zbMATH Keywords: blind source separation
zbMATH Keywords: adaptive algorithm
zbMATH Keywords: second-order cyclic statistics
zbMATH Keywords: convergence analysis
zbMATH Keywords: source detection
MaRDI profile type: Publication
cites work: Q3780804
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full work available at URL: https://doi.org/10.1007/bf01229991
OpenAlex ID: W2092748845
description: scientific article; zbMATH DE number 1422957