【摘要】 通过构造新的Lyapunov-Krasovskii泛函和线性矩阵不等式(linear matrix inequatity,LMI),研究变时滞非线性细胞神经网络渐近稳定性,利用牛顿-莱布尼兹公式,一些参数矩阵表达出系统变量之间的关系。从而得出一个具有变时滞相关的全局渐近稳定性判据,其扩展并改善了以前文献的结果。数值及仿真例子验证了结果的有效性。更多还原

【Abstract】 In this paper,a new Lyapunov-Krasovskii functional and the linear matrix inequatity(LMI)approach were proposed to deal with the problem of the global asymptotic stability of celluar neural networks with time-varying delay.Some parametermatrices were used to express the relationships among the system variables,and among the terms in Leibniz-Newton formula.As a result,an elegant delay dependent stability for neural networks with time-varying delay was derived that is a generatlization of,and an improvement over,previous criterions.The numerical example and simulation example demonstrate the effectiveness of the condition.更多还原