Impulses-induced exponential stability in recurrent delayed neural networks

Authors:
Quanjun Wu;Jin Zhou;Lan Xiang
Affiliations:
Department of Mathematics and Physics, Shanghai University of Electric Power, Shanghai 200090, China and Shanghai Institute of Applied Mathematics and Mechanics, Shanghai University, Shanghai 2000 ...;Shanghai Institute of Applied Mathematics and Mechanics, Shanghai University, Shanghai 200072, China;Department of Physics, School of Science, Shanghai University, Shanghai 200444, China
Venue:
Neurocomputing
Year:
2011

Citing 18
Cited 2

On delayed impulsive Hopfield neural networks

Neural Networks
On impulsive autoassociative neural networks

Neural Networks
Impulsive Systems and Control: Theory and Applications

Impulsive Systems and Control: Theory and Applications
Delay-dependent exponential stability analysis of delayed neural networks: an LMI approach

Neural Networks
Global exponential stability of delayed Hopfield neural networks

Neural Networks
Exponential stability of continuous-time and discrete-time cellular neural networks with delays

Applied Mathematics and Computation
Dynamics of periodic delayed neural networks

Neural Networks
Global exponential stability of recurrent neural networks with time-varying delays in the presence of strong external stimuli

Neural Networks
Global exponential stability of impulsive high-order BAM neural networks with time-varying delays

Neural Networks
Robust stability of stochastic delayed additive neural networks with Markovian switching

Neural Networks
State estimation for jumping recurrent neural networks with discrete and distributed delays

Neural Networks
Letters: Dynamics analysis of impulsive stochastic Cohen-Grossberg neural networks with Markovian jumping and mixed time delays

Neurocomputing
Exponential stability of impulsive delayed linear differential equations

IEEE Transactions on Circuits and Systems II: Express Briefs
Impulsive Effects on Stability of Fuzzy Cohen–Grossberg Neural Networks With Time-Varying Delays

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Time delays and stimulus-dependent pattern formation in periodic environments in isolated neurons

IEEE Transactions on Neural Networks
An analysis of global asymptotic stability of delayed cellular neural networks

IEEE Transactions on Neural Networks
An improved global asymptotic stability criterion for delayed cellular neural networks

IEEE Transactions on Neural Networks
Stability analysis for stochastic Cohen-Grossberg neural networks with mixed time delays

IEEE Transactions on Neural Networks

Stability analysis for impulsive coupled systems on networks

Neurocomputing
Synchronization of TS fuzzy complex dynamical networks with time-varying impulsive delays and stochastic effects

Fuzzy Sets and Systems

Quantified Score

Hi-index	0.01

Visualization

Abstract

The present paper formulates and studies a model of recurrent neural networks with time-varying delays in the presence of impulsive connectivity among the neurons. This model can well describe practical architectures of more realistic neural networks. Some novel yet generic criteria for global exponential stability of such neural networks are derived by establishing an extended Halanay differential inequality on impulsive delayed dynamical systems. The distinctive feature of this work is to address exponential stability issues without a priori stability assumption for the corresponding delayed neural networks without impulses. It is shown that the impulses in neuronal connectivity play an important role in inducing global exponential stability of recurrent delayed neural networks even if it may be unstable or chaotic itself. Furthermore, example and simulation are given to illustrate the practical nature of the novel results.