Exponential stability of impulsive discrete-time stochastic BAM neural networks with time-varying delay

Authors:
Gai Sun;Yu Zhang
Affiliations:
-;-
Venue:
Neurocomputing
Year:
2014

Citing 16
Cited 0

Bidirectional associative memories

IEEE Transactions on Systems, Man and Cybernetics
Stability of Time-Delay Systems

Stability of Time-Delay Systems
Global exponential stability of impulsive high-order BAM neural networks with time-varying delays

Neural Networks
Robust stability of discrete-time stochastic neural networks with time-varying delays

Neurocomputing
Stability and synchronization of discrete-time Markovian jumping neural networks with mixed mode-dependent time delays

IEEE Transactions on Neural Networks
On passivity analysis for stochastic neural networks with interval time-varying delay

Neurocomputing
On global exponential stability for impulsive cellular neural networks with time-varying delays

Computers & Mathematics with Applications
Robust global exponential synchronization of uncertain chaotic delayed neural networks via dual-stage impulsive control

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
On the exponential synchronization of stochastic impulsive chaotic delayed neural networks

Neurocomputing
Impulsive effects on stability of high-order BAM neural networks with time delays

Neurocomputing
Exponential stability of impulsive discrete systems with time delay and applications in stochastic neural networks: A Razumikhin approach

Neurocomputing
Impulsively synchronizing chaotic systems with delay and applications to secure communication

Automatica (Journal of IFAC)
Robust exponential stability of uncertain impulsive neural networks with time-varying delays and delayed impulses

Neurocomputing
Global asymptotic stability analysis of bidirectional associative memory neural networks with time delays

IEEE Transactions on Neural Networks
Adaptive Synchronization Between Two Different Chaotic Neural Networks With Time Delay

IEEE Transactions on Neural Networks
Stabilizing Effects of Impulses in Discrete-Time Delayed Neural Networks

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.01

Visualization

Abstract

In this paper, exponential stability of impulsive discrete-time stochastic bidirectional associative memory (BAM) neural networks with time-varying delay is investigated. Two sufficient conditions about exponential stability of this class of BAM neural networks are given by using difference inequalities and Lyapunov function together with Razumikhin technique. Some examples are also presented to illustrate the effectiveness and the advantage of the obtained results.