Paper Info
Title
Impulsive control for existence, uniqueness, and global stability of periodic solutions of recurrent neural networks with discrete and continuously distributed delays.
Abstract
In this paper, a class of recurrent neural networks with discrete and continuously distributed delays is considered. Sufficient conditions for the existence, uniqueness, and global exponential stability of a periodic solution are obtained by using contraction mapping theorem and stability theory on impulsive functional differential equations. The proposed method, which differs from the existing results in the literature, shows that network models may admit a periodic solution which is globally exponentially stable via proper impulsive control strategies even if it is originally unstable or divergent. Two numerical examples and their computer simulations are offered to show the effectiveness of our new results.
Year
DOI
Venue
2013
10.1109/TNNLS.2012.2236352
IEEE Trans. Neural Netw. Learning Syst.
Keywords
Field
DocType
stability theory,impulsive functional differential equations,periodic solution,neurocontrollers,uniqueness,asymptotic stability,contraction mapping theorem,global exponential stability,discrete distributed delays,recurrent neural networks,distributed control,periodic solutions,delays,impulsive control strategies,impulsive control,continuously distributed delays,recurrent neural nets,existence,differential equations,discrete systems,computer simulations,global stability
Applied mathematics,Computer science,Control theory,Recurrent neural network,Exponential stability,Artificial intelligence,Stability theory,Uniqueness,Differential equation,Contraction mapping,Pattern recognition,Periodic graph (geometry),Network model
Journal
Volume
Issue
ISSN
24
6
2162-2388
Citations 
PageRank 
References 
68
1.55
28
Authors
2
Name
Order
Citations
PageRank
Xiaodi Li141020.60
Shiji Song2124794.76