Boundedness and stability of nonautonomous cellular neural networks with reaction-diffusion terms

Authors:
Hongyong Zhao;Zisen Mao
Affiliations:
Department of Mathematics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, PR China;College of Science, PLA University of Science and Technology, Nanjing 211101, PR China
Venue:
Mathematics and Computers in Simulation
Year:
2009

Citing 5
Cited 2

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

Applied Mathematics and Computation
Exponential periodicity and stability of delayed neural networks

Mathematics and Computers in Simulation
Global stability analysis of a class of delayed cellular neural networks

Mathematics and Computers in Simulation
New conditions for global exponential stability of cellular neural networks with delays

Neural Networks
Exponential stability and periodic oscillatory of bi-directional associative memory neural network involving delays

Neurocomputing

Global exponential synchronization of generalized stochastic neural networks with mixed time-varying delays and reaction-diffusion terms

Neurocomputing
Original article: Attracting and invariant sets of non-autonomous reaction-diffusion neural networks with time-varying delays

Mathematics and Computers in Simulation

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we study a class of nonautonomous cellular neural networks with reaction-diffusion terms. By employing the method of variation parameter, applying inequality technique and introducing a lot of real parameters, we present some sufficient conditions ensuring the boundedness and globally exponential stability of the solutions for nonautonomous cellular neural networks with reaction-diffusion terms. The results obtained extend and improve the earlier publications. Finally, three examples with their numerical simulations are provided to show the correctness of our analysis.