The Use of Local Models Optimized by Genetic Programming Algorithms in Biomedical-Signal Analysis

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@InCollection{Brandejsky:2013:HBO,
  author =       "Tomas Brandejsky",
  title =        "The Use of Local Models Optimized by Genetic
                 Programming Algorithms in Biomedical-Signal Analysis",
  booktitle =    "Handbook of Optimization",
  publisher =    "Springer",
  year =         "2013",
  editor =       "Ivan Zelinka and Vaclav Snasel and Ajith Abraham",
  volume =       "38",
  series =       "Intelligent Systems Reference Library",
  chapter =      "28",
  pages =        "697--716",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-30503-0",
  URL =          "http://dx.doi.org/10.1007/978-3-642-30504-7_28",
  DOI =          "doi:10.1007/978-3-642-30504-7_28",
  bibdate =      "2013-09-25",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/series/isrl/isrl38.html#Brandejsky13",
  URL =          "http://dx.doi.org/10.1007/978-3-642-30504-7",
  abstract =     "Today researchers need to solve vague defined problems
                 working with huge data sets describing signals close to
                 chaotic ones. Common feature of such signals is missing
                 algebraic model explaining their nature. Genetic
                 Algorithms and Evolutionary Strategies are suitable to
                 optimise such models and Genetic Programming Algorithms
                 to develop them. Hierarchical GPA-ES algorithm
                 presented herein is used to build compact models of
                 difficult signals including signals representing
                 deterministic chaos. Efficiency of GPA-ES is presented
                 in the paper. Specific group of non-linearly composed
                 functions similar to real biomedical signals is studied
                 in the paper. On the base of these prerequisites,
                 models applicable in complex biomedical signals like
                 EEG modelling are formed and studied within the
                 contribution.",
  notes =        "CTU in Prague,",
}

Genetic Programming entries for Tomas Brandejsky

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