Global Robust Stability Criteria for Interval Delayed Full-Range Cellular Neural Networks

被引：17
作者：
Di Marco, Mauro [1 ]
Grazzini, Massimo [1 ]
Pancioni, Luca [1 ]
机构：
[1] Univ Siena, Dipartimento Ingn Informaz, I-53100 Siena, Italy
来源：
IEEE TRANSACTIONS ON NEURAL NETWORKS | 2011年 / 22卷 / 04期
关键词：
Cellular neural networks; differential variational inequalities; full-range model; global exponential stability; robust stability; QUADRATIC-PROGRAMMING PROBLEMS; EXPONENTIAL STABILITY; TIME DELAYS; CNNS;
D O I：
10.1109/TNN.2011.2110661
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This brief considers a class of delayed full-range (FR) cellular neural networks (CNNs) with uncertain interconnections between neurons modeled by means of intervalized matrices. Using mathematical tools from the theory of differential inclusions, a fundamental result on global robust stability of standard (S) CNNs is extended to prove global robust exponential stability for the corresponding class (same interconnection weights and inputs) of FR-CNNs. The result is of theoretical interest since, in general, the equivalence between the dynamical behavior of FR-CNNs and S-CNNs is not guaranteed.
引用
收藏
页码：666 / 671
页数：7
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