Global exponential convergence of periodic neural networks with time-varying delays

Authors:
Ailong Wu;Zhigang Zeng;Jine Zhang
Affiliations:
Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China and Key Laboratory of Image Processing and Intelligent Control of Education Minist ...;Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China and Key Laboratory of Image Processing and Intelligent Control of Education Minist ...;School of Basic Science, East China Jiaotong University, Nanchang 330013, China
Venue:
Neurocomputing
Year:
2012

Citing 13
Cited 0

Global exponential periodicity and global exponential stability of a class of recurrent neural networks with various activation functions and time-varying delays

Neural Networks
Positive invariant and global exponential attractive sets of neural networks with time-varying delays

Neurocomputing
Neural networks letter: On periodic solutions of neural networks via differential inclusions

Neural Networks
Convergence analysis of general neural networks under almost periodic stimuli

International Journal of Circuit Theory and Applications
Neural-network-based near-optimal control for a class of discrete-time affine nonlinear systems with control constraints

IEEE Transactions on Neural Networks
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
Multistability of recurrent neural networks with time-varying delays and the piecewise linear activation function

IEEE Transactions on Neural Networks
Global exponential stability in Lagrange sense for neutral type recurrent neural networks

Neurocomputing
Novel delay-dependent robust stability analysis for switched neutral-type neural networks with time-varying delays via SC technique

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Global exponential stability in Lagrange sense for periodic neural networks with various activation functions

Neurocomputing
New results on exponential attractivity of multiple almost periodic solutions of cellular neural networks with time-varying delays

Mathematical and Computer Modelling: An International Journal
Global exponential periodicity of a class of recurrent neural networks with oscillating parameters and time-varying delays

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

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.01

Visualization

Abstract

In this paper, the global exponential convergence of a general class of periodic neural networks with time-varying delays is investigated. Based on the theory of mixed monotone operator, a testable algebraic criteria for ascertaining global exponential convergence is derived. Furthermore, the rate of exponential convergence and bound of the networks are also estimated. Finally, a numerical example is given to show the effectiveness of the obtained results.