Carl S. Leichter

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The paper presents a novel model for classification of EEG data based on independent component analysis (ICA) as a feature extraction technique, and on evolving fuzzy neural networks ' as a classification modeling technique. One of the problems in such models is that some of EEG channels and model variables are redundant, 'noisy, and have a detrimental(More)
An adaptive model order estimation method for Independent Component Analysis (ICA) in EEG/MEG data is presented. This technique seeks to extract the minimum number of components necessary for effective Blind Source Separation (BSS). Experimental results using synthesized noisy MEG data demonstrate the utility of this technique. Model order estimation is(More)
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