Global synchronization in an array of discrete-time neural networks with nonlinear coupling and time-varying delays.
A general model for an array of discrete-time neural networks with hybrid coupling is proposed, which is composed of nonlinear coupling and time-varying delays. The coupling terms are described in terms of Lipchitz-type conditions that reflect more realistic dynamical behaviors of coupled systems in practice. The properties of Kronecker product are employed in order to pursue mathematical simplicity of dynamics analysis. On the basis of Lyapunov stability theory, an effective matrix functional is utilized to establish sufficient conditions under which the considered neural networks are globally synchronized. These conditions, which are dependent on the lower bound and the upper bound of the time-varying time delays, are expressed in terms of several linear matrix inequalities (LMIs), and therefore can be easily verified by utilizing the numerically efficient Matlab LMI toolbox. One illustrative example is given to justify the validity and feasibility of the proposed synchronization scheme.
Liang
Jinling
J
Department of Mathematics, Southeast University, Nanjing, 210096, China. jinlliang@gmail.com
Wang
Zidong
Z
Liu
Xiaohui
X
D000465:Algorithms; D005246:Feedback; D006801:Humans; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D011930:Reaction Time / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors