Classification of signals by means of Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Enrique Fernandez-Blanco and Daniel Rivero and 
                 Marcos Gestal and Julian Dorado",
  title =        "Classification of signals by means of Genetic
  journal =      "Soft Computing",
  year =         "2013",
  number =       "10",
  volume =       "17",
  pages =        "1929--1937",
  keywords =     "genetic algorithms, genetic programming, GP, Automatic
                 feature extraction Automatic classification Signal
  bibdate =      "2013-09-09",
  bibsource =    "DBLP,
  URL =          "",
  size =         "9 pages",
  abstract =     "This paper describes a new technique for signal
                 classification by means of Genetic Programming (GP).
                 The novelty of this technique is that no prior
                 knowledge of the signals is needed to extract the
                 features. Instead of it, GP is able to extract the most
                 relevant features needed for classification. This
                 technique has been applied for the solution of a
                 well-known problem: the classification of EEG signals
                 in epileptic and healthy patients. In this problem,
                 signals obtained from EEG recordings must be correctly
                 classified into their corresponding class. The aim is
                 to show that the technique described here, with the
                 automatic extraction of features, can return better
                 results than the classical techniques based on manual
                 extraction of features. For this purpose, a final
                 comparison between the results obtained with this
                 technique and other results found in the literature
                 with the same database can be found. This comparison
                 shows how this technique can improve the ones found.",

Genetic Programming entries for Enrique Fernandez-Blanco Daniel Rivero Cebrian Marcos Gestal Pose Julian Dorado