Global exponential stability of high-order neural networks with time-varying coefficients and delays

摘要：

The paper presents a sufficient condition ensuring global exponential stability for high-order neural networks with time-varying coefficients and delays. The result allows for the consideration of all unbounded neuron activation functions, while the previous results allowed for the consideration of bounded activation functions (|p?(x)| < 1, gt(x) < n,x). The method is based on basic analytical techniques and differential inequality techniques. The result of this paper is new and it complements previously known results. Several remarks are worked out to demonstrate the advantage of our result.

作者: Jie Zhou Huanxing Cai

作者单位: College of Science,Sichuan University of Science and Engineering Zigong,643000,P.R.China.

会议类型: 国际会议

会议名称: 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics(第二届智能人机系统与控制论国际学术会议 IHMSC 2010)

会议地点: 南京

会议语种:英文

页码: 523-526

在线出版日期: 2010-08-26（万方平台首次上网日期，不代表论文的发表时间）