用新的Lyapunov泛函处理带有离散时滞和分布时滞的神经网络的被动性

A New Lyapunov Functional Approach to Passivity Analysis for Neural Networks with Discrete and Distributed Delays

研究带有离散时滞和分布时滞的神经网络的被动性,通过构造新的Lyapunov泛函,建立了判定系统是被动的新标准.采用Lyapunov稳定理论、线性矩阵不等式及自由权矩阵等方法,通过实例很好地说明了所研究的结论是正确有效的,且在一定程度上降低了保守性.

This paper is concerned with the problem of passivity analysis for neural networks with discrete and distributed delays. By constructing novel Lyapunov functionals, a new passivity criteria is established to guarantee the passivity performance for the sys- tem. The work employs the Lyapunov stability theory and linear matrix inequality（LMI） approach, as well as the free weighting matri- ces method. Numerical examples are provided to demonstrate the feasibility of our conclusions. Moreover, it is proved that the results are less conservative than the existing ones.