%0 Journal Article
%T BMICA - Independent Component Analysis Based on B-Spline Mutual Information Estimator
%A Janett Walters-Williams
%A Yan Li
%J Signal & Image Processing
%D 2012
%I Academy & Industry Research Collaboration Center (AIRCC)
%X The information theoretic concept of mutual information provides a general framework to evaluatedependencies between variables. Its estimation however using B-Spline has not been used before in creatingan approach for Independent Component Analysis. In this paper we present a B-Spline estimator for mutualinformation 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 theĦ°renownĦħ FastICA.
%K B-Spline
%K Mutual Information
%K Independent Component Analysis
%K Reliability
%U http://airccse.org/journal/sipij/papers/3212sipij03.pdf