@inproceedings{ada744e994994e6c9134dce0af10fc0e,
title = "Evolving approximations for the Gaussian Q-function by genetic programming with semantic based crossover",
abstract = "The Gaussian Q-function is of great importance in the field of communications, where the noise is often characterized 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.",
author = "Phong, \{Dao Ngoc\} and Uy, \{Nguyen Quang\} and Hoai, \{Nguyen Xuan\} and McKay, \{R. I.\}",
year = "2012",
doi = "10.1109/CEC.2012.6256588",
language = "English",
isbn = "9781467315098",
series = "2012 IEEE Congress on Evolutionary Computation, CEC 2012",
booktitle = "2012 IEEE Congress on Evolutionary Computation, CEC 2012",
note = "2012 IEEE Congress on Evolutionary Computation, CEC 2012 ; Conference date: 10-06-2012 Through 15-06-2012",
}