多层单向耦合星形网络的特征值谱及同步能力分析

随着复杂网络同步的进一步发展,对复杂网络的研究重点由单层网络转向更加接近实际网络的多层有向网络.本文分别严格推导出三层、多层的单向耦合星形网络的特征值谱,并分析了耦合强度、节点数、层数对网络同步能力的影响,重点分析了层数和层间中心节点之间的耦合强度对多层单向耦合星形网络同步能力的影响,得出了层数对多层网络同步能力的影响至关重要.当同步域无界时,网络的同步能力与耦合强度、层数有关,同步能力随其增大而增强;当同步域有界时,对于叶子节点向中心节点耦合的多层星形网络,当层内耦合强度较弱时,层内耦合强度的增大会使同步能力增强,而层间叶子节点之间的耦合强度、层数的增大反而会使同步能力减弱;当层间中心节点之间的耦合强度较弱时,层间中心节点之间的耦合强度、层数的增大会使同步能力增强,层内耦合强度、层间叶子节点之间的耦合强度的增大反而会使同步能力减弱.对于中心节点向叶子节点耦合的多层星形网络,层间叶子节点之间的耦合强度、层数的增大会使同步能力增强,层内耦合强度、节点数、层间中心节点之间的耦合强度的增大反而会使同步能力减弱.     

基于局部序参数的电网同步性能优化

采用类Kuramoto模型对电网中的节点进行建模,利用局部序参数描述节点的局部同步能力.研究发现相比小功率节点,大功率节点到其直接邻居节点更难达到同步.提出一种网络耦合强度的非均匀分配方法,在网络总耦合强度不变的情况下,增大大功率节点到其直接邻居节点的耦合强度以及相关节点对之间的连边耦合强度,减少其余节点对间的耦合强度.研究表明,这种方法可以在一定范围内降低电网的同步临界耦合强度,改善网络的同步性能;但当这种耦合强度的非均匀性过大时,网络的同步性能开始恶化.     

基于时滞耦合映像格子的多耦合边耦合网络级联抗毁性研究

现实中各网络之间的耦合促进了网络间的交流,但也带来了级联故障大范围传播的风险.考虑到故障的传播一般存在时滞,并且一个节点可能拥有不止一条耦合边的情况,本文构建了基于时滞耦合映像格子的多耦合边无标度耦合网络级联故障模型.研究表明,对于BA(Barabási-Albert)无标度耦合网络,存在一个阈值hT≈3,当耦合强度小于此阈值时,耦合越强抗毁性越弱;反之,耦合越强抗毁性反而越强.另外,研究发现时滞对耦合网络的影响不仅仅是延长了故障传播的时间,为采取防护措施争取了时间,而且也对最终故障规模产生了影响,具体地,当层内时滞τ1和层间时滞τ2可取任意值时,当两者成整数倍关系时其最终故障规模将更大.本文的研究可为构建高抗毁性的耦合网络或提高耦合网络的级联抗毁性提供参考.     

大规模富社团网络的时空混沌同步

以Plankton时空混沌系统作为网络节点,通过非线性耦合构成富社团(rich-club,RC)网络,研究其时空混沌同步规律.首先给出了RC网络中连接节点之间的非线性耦合函数的一般性选取原则.进而基于Lyapunov稳定性定理,理论分析了实现网络同步的条件.最后,通过仿真模拟检验了网络的时空混沌同步效果.仿真研究表明,RC网络中各富节点之间以及这些富节点各自星形连接的子网络中的所有节点均实现了完全同步。     

叶子节点对于网络同步能力影响的研究

系统考察了叶子节点对于网络同步能力的影响,发现随着叶子节点比例的增加,网络的同步能力下降,同时给出了数值结果以及理论解释. 关键词： 复杂网络 叶子节点 同步能力     

非线性函数耦合的Chen吸引子网络的混沌同步

利用非对称非线性函数耦合混沌同步方法,讨论了Chen吸引子的混沌同步问题,数值模拟分析初始值和耦合强度因子的选择对于实现混沌同步的影响. 将非对称非线性函数耦合同步方法进一步推广发展到完全连接网络和由星形子网络构成的复杂大网络混沌同步的研究中. 提供了确定网络中神经元之间混沌同步状态稳定性的误差发展方程,并讨论各个耦合强度因子对网络同步稳定性过程的影响,给出了相应的稳定性范围. 通过数值模拟证明利用非线性函数作为耦合函数,实现完全连接网络、星形子网络构成大网络的混沌同步是有效的. 可以预测在网络的混沌同步 关键词： 非线性耦合函数 Chen吸引子 混沌同步 网络     

多个耦合星型网络的同步优化

本文讨论了星型网络中耦合Kuramoto振子的同步优化问题.分别考察具有随机频率分布叶子节点的单星型结构和多星型结构耦合网络达到同步所需的临界耦合强度.基于正弦函数的有界性导出的理论结果表明,单星型结构网络中,系统同步临界耦合强度与中心振子频率之间具有分段线性关系,而多星型结构耦合网络中,系统同步临界耦合强度与所有星型结构中心振子的频率之和保持分段线性关系.两种结构的网络的同步临界耦合强度最小值均在分段线性的转折点处.多星型结构耦合网络中,最小同步临界耦合强度出现在耦合系统只有一个同步集团的情形,而最大同步临界耦合强度出现在耦合系统有多个同步集团的情形.     

超混沌R?ssler系统构成的星形网络的混沌同步

通过对超混沌系统线性项与非线性项的适当分离配置，构造一个特殊的非线性耦合函数作为单元之间的耦合函数，提出非线性非对称耦合混沌同步方法，研究超混沌Rssler系统单元按照星形连接形式组成网络的同步问题.发现耦合强度在某一区域里存在着稳定的混沌同步现象.分析并讨论了不同参数在耦合过程中对混沌同步过程及其稳定性的影响.数值模拟结果证实该方法的有效性. 关键词： 超混沌同步 非线性耦合 R ssler系统 星形网络     

簇间连接方式不同的簇网络的同步过程研究

本文对簇间连接方式不同的三类簇网络的同步能力和同步过程进行研究. 构成簇网络的两个子网均为BA无标度网络, 当簇间连接方式是双向耦合时, 称其为TWD网络模型, 当簇间连接是大子网驱动小子网时, 称其为BDS网络模型, 当簇间连接是小子网驱动大子网时, 称其为SDB网络模型. 研究表明, 当小子网和大子网节点数目的比值大于某一临界值时, TWD网络模型的同步能力大于BDS网络模型的同步能力, 当该比值小于某一临界值时, TWD网络模型的同步能力小于BDS网络模型的同步能力, SDB网络模型的同步能力是三种网络结构中最差的. 对于簇间连接具有方向性的单向驱动网络, 簇网络的整体同步能力与被驱动子网的节点数和簇间连接数有关, 与驱动网络自身节点数无关. 增加簇间连接数在开始时会降低各子网的同步速度, 但最终各子网到达完全同步的时间减少, 网络的整体同步能力增强. 文中以Kuramoto相振子作为网络节点, 研究了不同情况下三种簇网络的同步过程, 证明了所得结论的正确性. 关键词： 簇网络 有向连接 同步能力 Kuramoto振子     

相邻耦合混沌振子的同步研究

通过对具有两个和三个节点的最近邻耦合网络同步的研究 ,发现随着网络的增大 ,最近邻耦合网络欲达到同步所需的耦合强度将不断增加。另外 ,通过李雅谱诺夫指数谱也证明了结论的正确性。     

Pinning-controlled synchronization of complex networks with bounded or unbounded synchronized regions

This paper studies pinning-controlled synchronization of complex networks with bounded or unbounded synchronized regions. To study a state-feedback pinning-controlled network with N nodes, it first converts the controlled network to an extended network of N+1 nodes without controls. It is shown that the controlled synchronizability of the given network is determined by the real part of the smallest nonzero eigenvalue of the coupling matrix of its extended network when the synchronized region is unbounded; but it is determined by the ratio of the real parts of the largest and the smallest nonzero eigenvalues of the coupling matrix when the synchronized region is bounded. Both theoretical analysis and numerical simulation show that the portion of controlled nodes has no critical values when the synchronized region is unbounded, but it has a critical value when the synchronized region is bounded. In the former case, therefore, it is possible to control the network to achieve synchronization by pinning only one node. In the latter case, the network can achieve controlled synchronization only when the portion of controlled nodes is larger than the critical value.     

Enhancing synchronizability by rewiring networks

<正>According to different forms of synchronized region,complex networks are divided into typeⅠ(unbounded synchronization region) and typeⅡ(bounded synchronization region) networks.This paper presents a rewiring algorithm to enhance the synchronizability of typeⅠand typeⅡnetworks.By utilizing the algorithm for an unweighted and undirected network,a better synchronizability of network with the same number of nodes and edges can be obtained. Numerical simulations on several different network models are used to support the proposed procedure.The relationship between different topological properties of the networks and the number of rewirings are shown.It finds that the final optimized network is independent of the initial network,and becomes homogeneous.In addition the optimized networks have similar structural properties in the sense of degree,and node and edge betweenness centralities.However,they do not have similar cluster coefficients for typeⅡnetworks.The research may be useful for designing more synchronizable networks and understanding the synchronization behaviour of networks.     

Explosive synchronization of multi-layer complex networks based on inter-layer star network connection

Explosive synchronization (ES) is a first-order transition phenomenon that is ubiquitous in various physical and biological systems. In recent years, researchers have focused on explosive synchronization in a single-layer network, but few in multi-layer networks. This paper proposes a frequency-weighted Kuramoto model in multi-layer complex networks with star connection between layers and analyzes the factors affecting the backward critical coupling strength by both theoretical analysis and numerical validation. Our results show that the backward critical coupling strength of each layer network is influenced by the inter-layer interaction strength and the average degree. The number of network layers, the number of nodes, and the network topology can not directly affect the synchronization of the network. Enhancing the inter-layer interaction strength can prevent the emergence of explosive synchronization and increasing the average degree can promote the generation of explosive synchronization.     

多层网络级联失效的预防和恢复策略概述

现实生活中,与国计民生密切相关的基础设施网络大多不是独立存在的,而是彼此之间相互联系或依赖的,于是用于研究这些系统的多层网络模型随之产生.多层网络中的节点在失效或者遭受攻击后会因"层内"和"层间"的相互作用而产生级联效应,从而使得失效能够在网络层内和层间反复传播并使得失效规模逐步放大.因此,多层网络比单个网络更加脆弱.多层网络级联失效产生的影响和损失往往是非常巨大的,所以对多层网络级联失效的预防和恢复的研究具有重大意义.就多层网络级联失效的预防而言,主要包含故障检测,保护重要节点,改变网络耦合机制和节点备份等策略.就多层网络发生级联失效后的恢复策略而言,主要包含共同边界节点恢复、空闲连边恢复、加边恢复、重要节点优先恢复、更改拓扑结构、局域攻击修复、自适应边修复等策略.     

Better synchronizability predicted by a new coupling method

In this paper, inspired by the idea that different nodes should play different roles in network synchronization, we bring forward a coupling method where the coupling strength of each node depends on its neighbors' degrees. Compared with the uniform coupled method and the recently proposed Motter-Zhou-Kurths method, the synchronizability of scale-free networks can be remarkably enhanced by using the present coupling method, and the highest network synchronizability is achieved at β=1 which is similar to a method introduced in [AIP Conf. Proc. 776, 201 (2005)].     

Double resonance in star networks of bistable units with disordered signals

It has been found that a hub node is better able to amplify weak external signals than leaf nodes in star networks. But hub-enhanced amplification is only attained by a single hub node and is limited to weak coupling strength. We show here that random initial phases in external weak signals do not affect the hub-enhanced amplification at weak coupling strength. Instead, they can improve the responses of all the leaf nodes to external signals at large coupling strength,resulting in a double resonance-like signal amplification. We use a reduced model to analyze the influence of the star structure and random initial phases on the emergence of double resonance.     

Synchronization of coupled logistic maps on random community networks

The collective synchronization of a system of coupled logistic maps on random community networks is investigated. It is found that the synchronizability of the community network is affected by two factors when the size of the network and the number of connections are fixed. One is the number of communities denoted by the parameter rn, and the other is the ratio σ of the connection probability p of each pair of nodes within each community to the connection probability q of each pair of nodes among different communities. Theoretical analysis and numerical results indicate that larger rn and smaller σ are the key to the enhancement of network synchronizability. We also testify synchronous properties of the system by analysing the largest Lyapunov exponents of the system.     

Cluster synchronization in networks of distinct groups of maps

In this paper, we study cluster synchronization in general bi-directed networks of nonidentical clusters, where all nodes in the same cluster share an identical map. Based on the transverse stability analysis, we present sufficient conditions for local cluster synchronization of networks. The conditions are composed of two factors: the common inter-cluster coupling, which ensures the existence of an invariant cluster synchronization manifold, and communication between each pair of nodes in the same cluster, which is necessary for chaos synchronization. Consequently, we propose a quantity to measure the cluster synchronizability for a network with respect to the given clusters via a function of the eigenvalues of the Laplacian corresponding to the generalized eigenspace transverse to the cluster synchronization manifold. Then, we discuss the clustering synchronous dynamics and cluster synchronizability for four artificial network models: (i) p-nearest-neighborhood graph; (ii) random clustering graph; (iii) bipartite random graph; (iv) degree-preferred growing clustering network. From these network models, we are to reveal how the intra-cluster and inter-cluster links affect the cluster synchronizability. By numerical examples, we find that for the first model, the cluster synchronizability regularly enhances with the increase of p, yet for the other three models, when the ratio of intra-cluster links and the inter-cluster links reaches certain quantity, the clustering synchronizability reaches maximal.