BMICA-independent component analysis based on B-spline mutual information estimator

Walters-Williams, Janett and Li, Yan (2012) BMICA-independent component analysis based on B-spline mutual information estimator. Signal and Image Processing, 3 (2). pp. 33-52. ISSN 2229-3922

Preview

PDF (Published Version) Walter-Williams_Li_PV.pdf Download (527Kb)

Abstract

The information theoretic concept of mutual information provides a general framework to evaluate dependencies between variables. Its estimation however using B-Spline has not been used before in creating an approach for Independent Component Analysis. In this paper we present a B-Spline estimator for mutual information to find the independent components in mixed signals. Tested using electroencephalography (EEG) signals the resulting BMICA (B-Spline Mutual Information Independent Component Analysis)
exhibits better performance than the standard Independent Component Analysis algorithms of FastICA, JADE, SOBI and EFICA in similar simulations. BMICA was found to be also more reliable than the 'renown' FastICA.

Statistics for this ePrint Item

Item Type:	Article (Commonwealth Reporting Category C)
Refereed:	Yes
Item Status:	Live Archive
Additional Information:	Open access journal.
Faculty / Department / School:	Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited:	25 Oct 2012 02:50
Last Modified:	03 Jul 2013 01:10
Uncontrolled Keywords:	B-spline; mutual information; independent component analysis; reliability
Fields of Research :	08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining 01 Mathematical Sciences > 0103 Numerical and Computational Mathematics > 010301 Numerical Analysis 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080199 Artificial Intelligence and Image Processing not elsewhere classified
Socio-Economic Objective:	E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI:	10.5121/sipij.2012.3203
URI:	http://eprints.usq.edu.au/id/eprint/21202

Actions (login required)

Archive Repository Staff Only