A Study of Exponential Stability of Multiple Equilibria in Delayed Recurrent Neural Networks

被引：0
|
作者：
Zeng, Zhigang [1 ]
Zheng, Wei Xing [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Dept Control Sci & Engn, Wuhan 430074, Hubei, Peoples R China
来源：
2012 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS 2012) | 2012年
关键词：
LINEAR TRANSFER-FUNCTIONS; ASSOCIATIVE MEMORIES; ACTIVATION FUNCTIONS; MULTISTABILITY; MULTIPERIODICITY;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The problem of exponential stability of multiple equilibria in recurrent neural networks with time-varying delays and concave-convex characteristics is addressed in this paper. The focus is placed upon derivation of some sufficient conditions under which an neural network of order n can have (2k + 2m - 1)(n) equilibrium points with (k + m)(n) of them having local exponential stability. The new results represent important extensions of the existing results on multistability of delayed recurrent neural networks.
引用
收藏
页码：2083 / 2086
页数：4
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