一类S分布时滞Hopfield神经网络的全局吸引性

Sufficient Condition for Global Attractivity of a Class of Hopfield Neural Networks With S-distributed Delays

摘要: 研究了一类具有S分布时滞的Hopfield神经网络的全局吸引性问题. 首先，通过常微分方程比较原理和适当的迭代证明了系统解的有界性，再通过一类非线性代数方程组和迭代技巧得到了平衡点全局吸引的一个充分条件. 最后，通过数值模拟验证了结论的有效性.

Abstract: Global attractivity of a class of Hopfield neural networks with S-distributed delays was studied in this paper. Based on a class of nonlinear algebraic equations and some computational techniques in M-matrix, a sufficient condition for global attractivity of the equilibrium of a class of Hopfield neural networks with S-distributed delays was obtained. Numerical simulations were given to illustrate validity of the result.