Open AccessStudy on the delayed feedback control of chaos in chaotic neural networks
Author(s) -
Gaiyun He,
Zhu Ping,
Hongping Chen,
Cao Zhi-Tong
Publication year - 2006
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.55.1040
Subject(s) - chaotic , artificial neural network , computer science , synchronization of chaos , control theory (sociology) , chaos (operating system) , control (management) , sequence (biology) , artificial intelligence , computer security , biology , genetics
Chaotic neural networks consisting of chaotic neurons exhibit rich dynamic behaviors and are expected to be used in information processing. But the output sequence of chaotic neural networks is chaotic, so the networks do not converge to a stable pattern. In order to apply chaotic neural networks to information search or pattern recognition, etc., it is necessary to control chaos in chaotic neural networks. In this paper, we propose an improved delayed feedback control method for chaotic neural networks. By means of the control method, computer simulation shows that controlled chaotic neural networks can converge to period-2 states between one stored pattern and its reverse pattern or various multiple-period states depending on the delay time.