Novel Delay-Dependent Stability Results for Neural Networks with Time-Varying Delays

被引：19
作者：
Shao, Hanyong [1 ]
机构：
[1] Qufu Normal Univ, Sch Elect & Informat Automat, Rizhao 276826, Shandong, Peoples R China
来源：
CIRCUITS SYSTEMS AND SIGNAL PROCESSING | 2010年 / 29卷 / 04期
关键词：
Recurrent neural network; Delay-dependent; Lyapunov functional; Globally exponentially stable; Linear matrix inequality (LMI); GLOBAL EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY; ROBUST STABILITY; CRITERIA; PERIODICITY;
D O I：
10.1007/s00034-010-9164-x
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：
This paper is concerned with the stability of static neural networks with time-varying delays. With the construction of a new Lyapunov functional and advanced techniques for calculating its derivative, a delay-dependent stability criterion is obtained that is less conservative than existing ones. A delay-independent criterion is also given that, together with the delay-dependent one, can be checked using recently developed algorithms. Examples are provided to illustrate the effectiveness and the reduced conservatism of the proposed results.
引用
收藏
页码：637 / 647
页数：11
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