The synchronization of complex dynamical networks as a basic problem, has been more and more concerned.
关于复杂动力网络的同步是其中的一个基本问题，越来越引起人们的兴趣。
Recently, complex dynamical networks have been widely concerned by many scientists from various fields and made great progress.
最近，复杂动力网络受到了不同学科的广泛关注并取得了重大进展。
Then, by constructing and applying certain pinning control schemes and adaptive laws, we study the cluster synchronization of complex dynamical networks.
其次，通过设计合适的牵制控制策略和自适应法则，研究了复杂动力网络上的聚类同步问题。
In this paper, we investigate the delayed impulsive synchronization of general complex delayed dynamical networks.
本文针对一般延迟的复杂动力网络，研究了脉冲采样时存在时滞的脉冲同步问题。
Firstly, based on the idea of delayed sampling impulses, a general complex delayed dynamical networks model with delayed impulses control is presented.
首先，基于脉冲采样时滞的思想，提出了具有时滞脉冲控制的一般延迟的复杂动力网络的模型。
In the present paper, two kinds of more general dynamical complex networks are considered.
在本文中，我们研究了具有时延的两种更一般的复杂动力网络。
As known to us all, one of the ultimate goals for studying complex networks is to understand the behaviors on dynamical processes occurring on them.
众所周知，人们研究复杂网络的终极目标之一是理解复杂网络上的动力学行为。
In this dissertation, we mainly discuss two dynamical behaviors of complex networks: the global stability of the equilibrium and the synchronization phenomenon.
在本文中，我们探讨了复杂网络模型的两种动力学行为：全局稳定性和同步。
Neural networks can implement fast parallel computation; meanwhile it has the characteristic of complex chaotic dynamical process, so it is one of the best choices to assist security chip design.
神经网络具备既能实现快速并行运算又有混沌动力学复杂行为的特征，是设计实现适用于实时安全通信应用的安全芯片最佳选择之一。
Neural networks can implement fast parallel computation; meanwhile it has the characteristic of complex chaotic dynamical process, so it is one of the best choices to assist security chip design.
神经网络具备既能实现快速并行运算又有混沌动力学复杂行为的特征，是设计实现适用于实时安全通信应用的安全芯片最佳选择之一。
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