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A method for classifying mental tasks in the space of EEG transforms

Amorim, R and Mirkin, B and Gan, JQ (2009) 'A method for classifying mental tasks in the space of EEG transforms.' In: UNSPECIFIED, (ed.) Proceedings of the UK Workshop on Computational Intelligence (UKCI 2009). University of Nottingham.

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Abstract

In this article we describe a new method for supervised classification of EEG signals. This method applies to the power spectrum density data and assigns class-dependent information weights to individual pixels, so that the decision is defined by the summary weights of the most informative pixel features. We experimentally analyze several versions of the approach. The informative features appear to be rather similar among different individuals, thus supporting the view that there are subject independent general brain patterns for the same mental task.

Item Type: Book Section
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Users 161 not found.
Date Deposited: 01 Jul 2013 13:38
Last Modified: 17 Aug 2017 18:07
URI: http://repository.essex.ac.uk/id/eprint/4154

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