Using distributed genetic programming to evolve classifiers for a brain computer interface

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{conf/esann/Alfaro-CidES06,
  title =        "Using distributed genetic programming to evolve
                 classifiers for a brain computer interface",
  author =       "Eva Alfaro-Cid and Anna Esparcia-Alc{\'a}zar and 
                 Ken Sharman",
  year =         "2006",
  booktitle =    "ESANN'2006 proceedings - European Symposium on
                 Artificial Neural Networks",
  editor =       "Michel Verleysen",
  pages =        "59--66",
  address =      "Bruges, Belgium",
  month =        "26-28 " # apr,
  bibdate =      "2006-08-30",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/conf/esann/esann2006.html#Alfaro-CidES06",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "2-930307-06-4",
  URL =          "http://www.dice.ucl.ac.be/Proceedings/esann/esannpdf/es2006-44.pdf",
  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