Finite-time exponential synchronization of reaction-diffusion delayed complex-dynamical networks

Abstract

This investigation looks at the issue of finite time exponential synchronization of complex dynamical systems with reaaction diffusion term. This reort studies complex networks consisting of N straightly and diffusively coupled networks. By building a new Lyapunov krasovskii functional (LKF), using Jensens inequality and convex algorithms approach stability conditions frameworks are determined. At last, a numerical precedent is given to demonstrate the practicality of the theoretical results.Complex dynamical systems (CDNs) have gotten impressive consideration because of their broad applications in useful society, for example, guideline of intensity framework, parallel picture preparing, the activity of no-man air vehicle, the acknowledgment of chain explosion, and so on., (see [12,35,27,2,3,5] and references in that). As of late, complex systems can be seen all over the place and are turning into an essential piece of our day by day life. The absolute most surely understood models incorporate nourishment networks, correspondence systems, interpersonal organizations, control matrices, cell systems, WWW, metabolic networks, illness transmission systems, and so on. Along these lines, the topology and dynamical conduct of complex dynamical systems have been broadly considered by the scientists ([8, 17, 21, 9]). Specifically, the synchronization issue of complex dynamical systems has gotten much concentration as of late ([34, 25]).

Global Asymptotic Stability of Competitive Neural Networks with Reaction-Diffusion Terms and Mixed Delays

“…Remark 1. In general, constructing a Lyapunov functional is a main research method for studying stability problems of neural networks, see [23][24][25][26][27]. However, constructing a proper Lyapunov functional is very difficult for obtaining the stability criteria of a complicated system.…”