Paper Info
Title
A new method for complete stability analysis of cellular neural networks with time delay.
Abstract
This paper presents new complete stability results for delayed cellular neural networks (DCNNs). A novel method is proposed for complete stability analysis of DCNNs. By applying the M-matrix theory and introducing some new estimation techniques on the solutions of DCNNs, a simple and improved complete stability criterion is derived. The new criterion unifies the delay-dependent and delay-independent complete stability conditions for DCNNs. Moreover, the obtained delay-dependent criterion can give a larger upper bound of the time delay than the existing ones such that the complete stability can still be retained. Numerical examples are presented which show that the new complete stability results for DCNNs are compared favorably with the existing results.
Year
DOI
Venue
2010
10.1109/TNN.2010.2048925
IEEE Transactions on Neural Networks
Keywords
DocType
Volume
time delay,delay-independent complete stability condition,new complete stability result,new criterion,delay dependent,asymptotic stability,complete stability,estimation techniques,new estimation technique,m-matrix theory,matrix algebra,delay independent,cellular neural networks,m-matrix,time-delay,delays,cellular neural network,cellular neural nets,delay-independent/delay-dependent criterion,existing result,complete stability analysis,improved complete stability criterion,stability analysis,delay-dependent criterion,new method,cellular neural networks (cnns),matrix theory,algorithms,mathematics,computer simulation,m matrix,neural networks,upper bound,image processing
Journal
21
Issue
ISSN
Citations 
7
1941-0093
33
PageRank 
References 
Authors
1.29
15
2
Name
Order
Citations
PageRank
Wu-Hua Chen186958.24
Wei Xing Zheng24266274.73