Exponential stability of reaction-diffusion high-order Markovian jump Hopfield neural networks with time-varying delays期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

按检索

Exponential stability of reaction-diffusion high-order Markovian jump Hopfield neural networks with time-varying delays

Authors:	Yangfan Wang Ping LinLinshan Wang

Institution:	^a Division of Mathematics, University of Dundee, Dundee, DD1 4HN, UK ^b Department of Mathematics, Ocean University of China, Qingdao, 266071, China ^c Department of Mathematics, Liaocheng University, Liaocheng, 252059, China ^d Department of Mathematics and Mechanics, University of Science and Technology Beijing (USTB), Beijing, 100083, China ^e College of Marine Life Sciences, Ocean University of China, Qingdao, 266071, China

Abstract:	This paper studies the problems of global exponential stability of reaction-diffusion high-order Markovian jump Hopfield neural networks with time-varying delays. By employing a new Lyapunov-Krasovskii functional and linear matrix inequality, some criteria of global exponential stability in the mean square for the reaction-diffusion high-order neural networks are established, which are easily verifiable and have a wider adaptive. An example is also discussed to illustrate our results.

Keywords:	Reaction-diffusion high-order Hopfield neural networks Time-varying delays Markovian jump Linear matrix inequalities Exponential stability in the mean square
本文献已被 ScienceDirect 等数据库收录！