A New Set of Sufficient Conditions Based on Coupling Parameters for Synchronization of Hopfield like Chaotic Neural Networks

被引：0
|
作者：
Mahdavi, Nariman [1 ]
Menhaj, Mohammad Bagher [1 ]
机构：
[1] Amir Kabir Univ Technol, Dept Elect Engn, Tehran, Iran
来源：
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | 2011年 / 9卷 / 01期
关键词：
Chaos synchronization; chaotic neural network; logistic map; stabilization; COMPLEX DYNAMICAL NETWORKS; BASIC DYNAMICS; OSCILLATIONS; CIRCUITS; SYSTEMS; EEG;
D O I：
10.1007/s12555-011-0113-7
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we consider a Hopfield like Chaotic Neural Networks which have both self-coupling and non-invertible activation functions. We show that the interactions between neurons can be used as a means of chaos generation or suppression to neuron's outputs when more adaptability or stability is required. Furthermore, a new set of sufficient conditions based on coupling weights is proposed so that the synchronization of all neuron's outputs with each other is guaranteed, when all neuron's have identical activation functions. Finally, the effectiveness of the proposed approach is evaluated by performing simulations on three illustrative examples.
引用
收藏
页码：104 / 111
页数：8
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