Global Exponential Stability of Delayed Hopfield Neural Networks
In this paper,we have derived some sufficient conditions for existence and uniqueness of equilibrium and global exponential stability in delayed Hopfield neural networks by using a different approach irom the usually used one where the existence,uniqueness of equilibrium and stability are proved in two separate steps,rather we first prove global exponential convergence to 0 of the difference between any two solutions of the original neural networks,the existence and uniqueness of equilibrium is the direct results of this procedure. We obtain the conditions by suitable construction of Lyapunov functions and estimation of derivates of the Lyapunov functions by the well-known Youngs inequality and Holders inequality. The proposed conditions are related to p-norms of vector or matrix,p∈ l,∞),and thus unify and generalize some results in the literature.
Global exponential stability Delayed Hopfield neural networks p-Norms
Jifu Nong
College of Mathematics and Computer Science,Guangxi University for Nationalities,Nanning,China Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis,Nanning,China
国际会议
西安
英文
1761-1765
2011-12-23（万方平台首次上网日期，不代表论文的发表时间）