@inproceedings{63ac5f10af69454884120d2af354cd5b,
title = "Improved transiently chaotic neural network and its application to optimization",
abstract = "A wavelet function was introduced into the activation function of the transiently chaotic neural network in order to solve combinational optimization problems more efficiently. The dynamic behaviors of chaotic signal neural units were analyzed and the time evolution figures of the maximal Lyapunov exponents and chaotic dynamic behavior were given. The improved transiently chaotic neural network has the ability to stay in chaotic states longer because the wavelet function is non-monotonous and is a kind of basic function. The simulation results prove that the improved transiently chaotic neural network is superior to the original in solving 10-city traveling salesman problem (TSP).",
author = "Xu, \{Yao Qun\} and Ming Sun and Guo, \{Meng Shu\}",
year = "2006",
doi = "10.1007/11893257\_113",
language = "英语",
isbn = "3540464816",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "1032--1041",
booktitle = "Neural Information Processing - 13th International Conference, ICONIP 2006, Proceedings",
address = "德国",
note = "13th International Conference on Neural Information Processing, ICONIP 2006 ; Conference date: 03-10-2006 Through 06-10-2006",
}