Exponential networked synchronization of master-slave chaotic systems with time-varying communication topologies

The networked synchronization problem of a class of master-slave chaotic systems with time-varying communication topologies is investigated in this paper. Based on algebraic graph theory and matrix theory, a simple linear state feedback controller is designed to synchronize the master chaotic system and the slave chaotic systems with a time- varying communication topology connection. The exponential stability of the closed-loop networked synchronization error system is guaranteed by applying Lyapunov stability theory. The derived novel criteria are in the form of linear matrix inequalities (LMIs), which are easy to examine and tremendously reduce the computation burden from the feedback matrices. This paper provides an alternative networked secure communication scheme which can be extended conveniently. An illustrative example is given to demonstrate the effectiveness of the proposed networked synchronization method.     

一类参数不确定统一混沌系统的脉冲滞后同步

针对一类具有传输信道时间延迟且参数不确定的统一混沌系统，提出了一种脉冲控制同步方法.该方法将两个非自治混沌系统之间脉冲同步的实用稳定性问题转化为同步误差系统在原点的实用稳定性问题，基于脉冲微分方程的相关理论，给出了同步误差系统在原点的实用稳定判据，仿真结果验证了方法的有效性. 关键词： 统一混沌系统 混沌同步 脉冲控制 实用稳定性     

耦合系统的混沌相位同步

通过引入混沌运动的相位定义分析了线性和非线性耦合参数对两个主共振子系统之间的混沌相位同步的影响.讨论了在近似于主共振条件下,两子系统不同步、不完全相位同步和完全相位同步之间的演化过程,揭示了不同状态相互转化与Lyapunov指数变化之间的关系,指出随着线性耦合力的增加,相位同步效应增强,然而随着非线性耦合力的增加,相位同步效应减弱. 关键词： 相位同步 Rssler振子 耦合 Lyapunov指数     

Control and synchronization of second Julia sets

A visualization of Julia sets of the complex Henon map system with two complex variables is introduced in this paper.With this method,the optimal control function method is introduced to this system and the control and synchronization of its Julia sets are achieved.Control and synchronization of generalized Julia sets are also achieved with this optimal control method.The simulations illustrate the efficacy of this method.     

高可靠分布式容错计算机架构的研究

分布式系统因其具有分散安装、可靠性高、扩展性好、维修成本低、健壮、安全等诸多优点,国内外相继开展分布式计算机高可靠性技术的研究。本文提出了高可靠分布式容错计算机的构架设计思路,并对TTE总线的选用进行了分析论证,重点描述了成员一致性保证和余度同步等关键技术。     

Complete and phase synchronization in a heterogeneous small-world neuronal network

Synchronous firing of neurons is thought to be important for information communication in neuronal networks. This paper investigates the complete and phase synchronization in a heterogeneous small-world chaotic Hindmarsh--Rose neuronal network. The effects of various network parameters on synchronization behaviour are discussed with some biological explanations. Complete synchronization of small-world neuronal networks is studied theoretically by the master stability function method. It is shown that the coupling strength necessary for complete or phase synchronization decreases with the neuron number, the node degree and the connection density are increased. The effect of heterogeneity of neuronal networks is also considered and it is found that the network heterogeneity has an adverse effect on synchrony.     

用单一驱动变量同步混沌与超混沌的一种方法

为减少混沌或超混沌同步过程中所需同步信号的个数以及提高同步的效率，提出了用线性可逆变换的方法重组系统，从而使原来不能同步的系统实现了只用单一信号就可同步的目的-另外，也大大提高系统的同步速率- 关键词： 线性可逆变换 混沌和超混沌同步 最大条件Lyapunov指数     

Modified Projective Synchronization of a New Hyperchaotic System via Nonlinear Control

In this paper, a nonlinear control scheme of two identical hyperchaotic Chensystems is developed to realize their modified projective synchronization.We achieve modified projective synchronization between the two identicalhyperchaotic systems by directing the scaling factor onto the desired value. With symbolic computation system Maple and Lyapunov stability theory, numerical simulations are given to perform the process of the synchronization.     

参数未知的不同阶数混沌系统广义同步及参数估计

采用扩阶方法(使响应系统和驱动系统的维数相同)，把不同阶数混沌系统的广义同步问题转化为相同阶数混沌系统之间的广义同步，基于Lyapunov稳定性定理和自适应控制方法(用于相同阶数混沌系统的同步)，给出了自适应控制器和参数自适应律，进而实现了不同阶数混沌系统的广义同步.将该方法应用于参数未知的超Lü，Lorenz，广义Lorenz和Liu等系统之间的广义混沌同步，理论证明了该方法可以使这些系统达到渐近广义同步，并且可以辨识驱动系统和响应系统的所有参数，数值模拟进一步证明了该方法的有效性.     

FitzHugh-Nagumo神经元网络的联想记忆与分割

以广泛讨论的Fitz Hugh-Nagumo神经元节点组成脉动神经元网络,从神经系统空时模式编码理论研究网络的记忆(或模式)存储与时间分割问题.给定一个输入模式,它是几种模式的叠加,网络能够以一部分神经元同步发放的形式一个接一个地分割出每一种模式.如果输入的模式有缺损,系统能够把它们恢复成原型,即神经网络的联想记忆功能.模拟需要调节耦合强度和噪声强度等参数使得网络在特定的参数值和中等强度噪声达到最优的时间分割,与广泛讨论的随机共振现象一致.