论文信息 - Global exponential stability of Hopfield neural networks with distributed delays

Global exponential stability of Hopfield neural networks with distributed delays

In this paper, dynamical behaviors of Hopfield neural networks system with distributed delays were studied. By using contraction mapping principle and differential inequality technique, a sufficient condition was obtained to ensure the existence uniqueness and global exponential stability of the equilibrium point for the model. Here we point out that our methods, which are different from previous known results, base on the contraction mapping principle and inequality technique. Two remarks were also worked out to demonstrate the advantage of our results.

Shuyong Li | Jie Zhou | Zhiguo Yang

[1] Hongyong Zhao,et al. Global asymptotic stability of Hopfield neural network involving distributed delays , 2004, Neural Networks.

[2] Hongyong Zhao,et al. Global exponential stability and periodicity of cellular neural networks with variable delays , 2005 .

[3] K. Gopalsamy,et al. Stability in asymmetric Hopfield nets with transmission delays , 1994 .

[4] Qiang Zhang,et al. Global exponential stability of Hopfield neural networks with continuously distributed delays , 2003 .

[5] Réjean Plamondon,et al. On the stability analysis of delayed neural networks systems , 2001, Neural Networks.

[6] Yuehua Yu,et al. Global exponential stability of cellular neural networks with continuously distributed delays and impulses , 2006 .

[7] Xuesong Jin,et al. Global stability analysis in delayed Hopfield neural network models , 2000, Neural Networks.

[8] Yumei Huang,et al. On Equilibrium and Stability of a Class of Neural Networks with Mixed Delays , 2006, ISNN.

[9] J J Hopfield,et al. Neurons with graded response have collective computational properties like those of two-state neurons. , 1984, Proceedings of the National Academy of Sciences of the United States of America.