This paper deals with the global asymptotic stability problem for Hopfield neural networks with time-varying delays. By resorting to the integral inequality and constructing a Lyapunov-Krasovskii functional, a novel delay-dependent condition is established to guarantee the existence and global asymptotic stability of the unique equilibrium point for a given delayed Hopfield neural network. This criterion is expressed in terms of linear matrix inequalities （LMIs）, which can be easily checked by utilizing the recently developed algorithms for solving LMIs. Examples are provided to demonstrate the effectiveness and reduced conservatism of the proposed condition.
基于加权网络特性,以Internet网络为例,提出了一种基于节点度和边权值比率(Degree and Weighted Ratio,DWR)的搜索算法。通过理论分析与仿真实验得出:DWR搜索算法在搜索时间和搜索代价上均优于最大度搜索算法和最大局部介数搜索算法。通过数值仿真分析发现,DWR搜索算法的搜索时间随着设置参数的增大而逐渐增大。因此,在Internet网络中,DWR搜索算法既可以提高网络信息传输的速度,又可以增强网络的传输能力。
In this paper, a consensus algorithm of multi-agent second-order dynamical systems with nonsymmetric interconnection and heterogeneous delays is studied. With the hypothesis of directed weighted topology graph with a globally reachable node, decentralized consensus condition is obtained by applying generalized Nyquist criterion. For the systems with both communication and input delays, it is shown that the consensus condition is dependent on input delays but independent of communication delays.
