Dynamics Analysis of a Class of Memristor-Based Recurrent Networks with Time-Varying Delays in the Presence of Strong External Stimuli

被引：83
作者：
Wen, Shiping [1 ,2 ]
Zeng, Zhigang [1 ,2 ]
机构：
[1] Educ Minist China, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Dept Control Sci & Engn, Wuhan 430074, Peoples R China
来源：
NEURAL PROCESSING LETTERS | 2012年 / 35卷 / 01期
基金：
高等学校博士学科点专项科研基金;
关键词：
Memristor; Recurrent networks; Global exponential stability; GLOBAL EXPONENTIAL STABILITY; HOPFIELD NEURAL-NETWORKS; ASYMPTOTIC STABILITY; ROBUST STABILITY; DISTRIBUTED DELAYS; ACTIVATIONS; PARAMETERS;
D O I：
10.1007/s11063-011-9203-z
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we investigate the dynamics problem about the memristor-based recurrent network with bounded activation functions and bounded time-varying delays in the presence of strong external stimuli. It is shown that global exponential stability of such networks can be achieved when the external stimuli are sufficiently strong, without the need for other conditions. A sufficient condition on the bounds of stimuli is derived for global exponential stability of memristor-based recurrent networks. And all the results are in the sense of Filippov solutions. Simulation results illustrate the uses of the criteria to ascertain the global exponential stability of specific networks.
引用
收藏
页码：47 / 59
页数：13
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