Using distributed genetic programming to evolve classifiers for a brain computer interface
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{conf/esann/Alfaro-CidES06,
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title = "Using distributed genetic programming to evolve
classifiers for a brain computer interface",
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author = "Eva Alfaro-Cid and Anna Esparcia-Alc{\'a}zar and
Ken Sharman",
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year = "2006",
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booktitle = "ESANN'2006 proceedings - European Symposium on
Artificial Neural Networks",
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editor = "Michel Verleysen",
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pages = "59--66",
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address = "Bruges, Belgium",
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month = "26-28 " # apr,
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bibdate = "2006-08-30",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/esann/esann2006.html#Alfaro-CidES06",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "2-930307-06-4",
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URL = "http://www.dice.ucl.ac.be/Proceedings/esann/esannpdf/es2006-44.pdf",
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abstract = "The objective of this paper is to illustrate the
application of genetic programming to evolve
classifiers for multi-channel time series data. The
paper shows how high performance distributed genetic
programming (GP) has been implemented for evolving
classifiers. The particular application discussed
herein is the classification of human
electroencephalographic (EEG) signals for a
brain-computer interface (BCI). The resulting
classifying structures provide classification rates
comparable to those obtained using traditional,
human-designed, classification",
-
notes = "http://www.dice.ucl.ac.be/Proceedings/esann/",
- }
Genetic Programming entries for
Eva Alfaro-Cid
Anna Esparcia-Alcazar
Kenneth C Sharman
Citations