@inproceedings{c0013bf112994d318e74e4d5a99adc62,
title = "Multi-valued neural network trained by differential evolution for synthesizing multiple-valued functions",
abstract = "We consider the problem of synthesizing multiple valued logic (MVL) functions by neural networks. A differential evolution algorithm is proposed to train the learnable multiple valued logic network. The optimum window and biasing parameters to be chosen for convergence are derived. Experiments performed on benchmark problems demonstrate the convergence and robustness of the network. Preliminary results indicate that differential evolution is suitable to train MVL networks for synthesizing MVL functions.",
author = "Huiqin Chen and Sheng Li and Qian Shi and Dongmei Shen and Shangce Gao",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015 ; Conference date: 24-04-2015 Through 26-04-2015",
year = "2015",
month = jun,
day = "9",
doi = "10.1109/ICISCE.2015.80",
language = "英語",
series = "Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "332--335",
editor = "Shaozi Li and Ying Dai and Yun Cheng",
booktitle = "Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015",
}