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Multi-objective evolutionary methods for channel selection in Brain-Computer Interfaces: Some preliminary experimental results

Hasan, BAS and Gan, JQ and Zhang, Q (2010) Multi-objective evolutionary methods for channel selection in Brain-Computer Interfaces: Some preliminary experimental results. In: UNSPECIFIED, ? - ?.

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Abstract

This paper presents a comparative study among three evolutionary and search based methods to solve the problem of channel selection for Brain-Computer Interface (BCI) systems. Multi-Objective Particle Swarm Optimization (MOPSO) method is compared to Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) and single objective Sequential Floating Forward Search (SFFS) method. The methods are tested on the first data set for BCI-Competition IV. The results show the usefulness of the multi-objective evolutionary methods in achieving accuracy results similar to the extensive search method with fewer channels and less computational time. © 2010 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Users 161 not found.
Date Deposited: 12 Dec 2012 21:04
Last Modified: 30 Jan 2019 16:23
URI: http://repository.essex.ac.uk/id/eprint/4138

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