Evolving Approximations for the Gaussian Q-function by Genetic Programming with Semantic Based Crossover
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Dao:2012:CEC,
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title = "Evolving Approximations for the {Gaussian Q-function}
by Genetic Programming with Semantic Based Crossover",
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author = "Ngoc Phong Dao and {Quang Uy Nguyen} and
{Xuan Hoai Nguyen} and R I (Bob) McKay",
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pages = "2515--2520",
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booktitle = "Proceedings of the 2012 IEEE Congress on Evolutionary
Computation",
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year = "2012",
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editor = "Xiaodong Li",
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month = "10-15 " # jun,
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DOI = "doi:10.1109/CEC.2012.6256588",
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address = "Brisbane, Australia",
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ISBN = "0-7803-8515-2",
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keywords = "genetic algorithms, genetic programming, Computational
Intelligence in Communications and Networking
(IEEE-CEC), Real-world applications",
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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.",
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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
Citations