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• W183711431 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." @default.
• W183711431 created "2016-06-24" @default.
• W183711431 creator A5044298426 @default.
• W183711431 date "2012-04-30" @default.
• W183711431 modified "2023-10-01" @default.
• W183711431 title "BMICA - Independent Component Analysis Based on B-Spline Mutual Information Estimator" @default.
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• W183711431 doi "https://doi.org/10.5121/sipij.2012.3203" @default.
• W183711431 hasPublicationYear "2012" @default.
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