Evolving Approximations for the Gaussian Q-function by Genetic Programming with Semantic Based Crossover

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  title =        "Evolving Approximations for the {Gaussian Q-function}
                 by Genetic Programming with Semantic Based Crossover",
  author =       "Ngoc Phong Dao and {Quang Uy Nguyen} and 
                 {Xuan Hoai Nguyen} and R I (Bob) McKay",
  pages =        "2515--2520",
  booktitle =    "Proceedings of the 2012 IEEE Congress on Evolutionary
  year =         "2012",
  editor =       "Xiaodong Li",
  month =        "10-15 " # jun,
  DOI =          "doi:10.1109/CEC.2012.6256588",
  address =      "Brisbane, Australia",
  ISBN =         "0-7803-8515-2",
  keywords =     "genetic algorithms, genetic programming, Computational
                 Intelligence in Communications and Networking
                 (IEEE-CEC), Real-world applications",
  abstract =     "The Gaussian Q-function is of great importance in the
                 field of communications, where the noise is often
                 characterised by the Gaussian distribution. However, no
                 simple exact closed form of the Q-function is known.
                 Consequently, a number of approximations have been
                 proposed over the past several decades. In this paper,
                 we use Genetic Programming with semantic based
                 crossover to approximate the Q-function in two forms:
                 the free and the exponential forms. Using this form, we
                 found approximations in both forms that are more
                 accurate than all previous approximations designed by
                 human experts.",
  notes =        "WCCI 2012. CEC 2012 - A joint meeting of the IEEE, the
                 EPS and the IET.",

Genetic Programming entries for Ngoc Phong Dao Quang Uy Nguyen Nguyen Xuan Hoai R I (Bob) McKay