Lagrange Stability of Memristive Neural Networks With Discrete and Distributed Delays

被引：179

作者：

Wu, Ailong ^{[1
,2
,3
]}

Zeng, Zhigang ^{[3
,4
]}

机构：

[1] Hubei Normal Univ, Coll Math & Stat, Huangshi 435002, Peoples R China

[2] Xi An Jiao Tong Univ, Inst Informat & Syst Sci, Xian 710049, Peoples R China

[3] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Peoples R China

[4] Educ Minist China, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Peoples R China

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS | 2014年 / 25卷 / 04期

关键词：

Hybrid systems; Lagrange stability; memristive neural networks; nonsmooth analysis; GLOBAL EXPONENTIAL STABILITY; ROBUST STATE ESTIMATION; SYNCHRONIZATION; SYSTEMS; SENSE; SETS;

D O I：

10.1109/TNNLS.2013.2280458

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Memristive neuromorphic system is a good candidate for creating artificial brain. In this paper, a general class of memristive neural networks with discrete and distributed delays is introduced and studied. Some Lagrange stability criteria dependent on the network parameters are derived via nonsmooth analysis and control theory. In particular, several succinct criteria are provided to ascertain the Lagrange stability of memristive neural networks with and without delays. The proposed Lagrange stability criteria are the improvement and extension of the existing results in the literature. Three numerical examples are given to show the superiority of theoretical results.

引用

页码：690 / 703

页数：14

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