基于符号向量动力学的耦合映像格子初始向量估计

在符号动力学的基础上,探讨了基于符号向量序列的局部耦合映像格子求逆问题,证明了相空间I^N上任意取值通过基于符号向量序列的逆迭代过程必然收敛至初始向量,提出了基于符号向量动力学的初始向量估计算法,从而建立了耦合映像格子符号序列和实际动力系统相空间的对应关系.实验结果表明,根据该算法可以有效建立符号向量序列和耦合映像格子相空间之间的对应关系,更好地刻画了实际模型的物理过程. 关键词： 耦合映像格子 符号动力学 初始向量估计     

基于符号向量动力学的耦合映像格子参数估计

本文,将符号动力学推广到耦合映像格子中,以Logistic映射下耦合映像格子为研究对象,研究控制参数对符号向量序列动力学特性的影响.通过研究耦合映像格子逆函数,给出耦合映像格子的遍历条件.进一步,将给出系统初始向量,禁止字以及控制参数的符号向量序列描述方法,并最终给出基于符号向量动力学的耦合映像格子控制参数估计方法.实验结果表明,根据本文算法可以有效建立符号序列和耦合映像格子控制参数之间的对应关系,能够更好地刻画了实际模型的物理过程. 关键词： 符号向量动力学 耦合映像格子 参数估计 遍历性     

基于时变耦合映像格子模型的信号初值估计

从耦合映像格子中,恢复系统初始条件是耦合系统求逆问题,也是信号处理研究中的一个关键性问题.本文在符号动力学方法的基础上,对映像系数进行修正,针对耦合单峰Logistic映射,提出一种基于时变映像系数恢复信号初值的新方法.在映像过程无噪或受到高斯白噪声污染时,本文方法都能够较好地恢复信号初值的统计特性,而且具有较小的偏差和均方误差,并与原信号之间具有较强的相关性,从而能够更好和更加合理地刻画实际信号的物理过程,对系统初值做出更优的估计. 关键词： 耦合映像格子 恢复初值的统计特性 时变映像系数     

基于可变参数双向耦合映像系统的时空混沌Hash函数设计

在分析单向与双向耦合映像格子系统的初值与参数敏感性的基础上，提出了一种基于可变参数双向耦合映像系统的时空混沌单向Hash函数构造方案.该方案以耦合映像系统的部分初态作为密钥，在迭代过程中, 通过上一次的迭代值和线性变换后的不同位置的明文消息比特动态确定双向耦合映像系统模型参数，将明文消息多格点并行注入时空混沌轨迹中；取迭代序列中最后一轮迭代结果的适当空间项，线性映射为Hash值要求的128 bit值.由于耦合映像系统的双向扩散机理与混乱作用，迭代过程具有极强的不可逆性及初值与参数敏感性，Hash结果的每位都与明文及密钥有着敏感、复杂的非线性强耦合关系.仿真实验与分析结果表明，该算法达到了Hash函数的各项性能要求，安全性好，执行效率高. 关键词： Hash函数 时空混沌 耦合映像格子     

基于时空混沌系统的单向Hash函数构造

提出了一种基于时空混沌系统的Hash函数构造方法.以线性变换后的消息数作为一组初值来驱动单向耦合映像格子的时空混沌系统，产生时空混沌序列，取其空间最后一组混沌序列的适当项，线性映射为Hash值要求的128bit值.研究结果表明，这种基于时空混沌系统的Hash函数具有很好的单向性、弱碰撞性、初值敏感性，较基于低维混沌映射的Hash函数具有更强的保密性能，且实现简单. 关键词： 时空混沌 Hash函数 单向耦合映像格子     

基于多重耦合映像格子的信号初值恢复研究

利用耦合映像格子恢复信号初值是信号处理研究中一个重要的问题.耦合映像格子具有混沌系统的初值敏感性，当初值受到噪声污染时将会影响到系统对其的恢复.提出了一种由多个一维耦合映像格子系统并列耦合而成的多重耦合映像格子系统，通过将多个一维系统耦合，使因受到噪声干扰而趋向于指数分离的混沌轨道相互靠近，以达到抑制噪声的目的.数值仿真表明，该系统具有较强的抗噪声能力和较高的鲁棒性.在耦合系数选取适当的情况下，即使初始信号受到噪声干扰，该多重耦合系统仍然能够很好地恢复信号初值的统计特性，且对单个初值的恢复情况及与初始信号 关键词： 耦合映像格子 恢复信号的统计特性 多重耦合     

一个全局耦合不连续映像格子中的冻结化随机图案模式

本文研究了一类既不连续又不可逆分段线性映像构成的全局耦合映像格子系统中的一类典型集体动力学行为, 即冻结化随机图案模式. 计算了平均同步序参量和最大李雅普诺夫指数随耦合强度的变化. 结果显示, 当耦合强度超过某个阈值后, 在给定动力学变量的初始下, 系统几乎都能达到完全或部分同步状态, 出现冻结化随机图案. 这些现象表明, 耦合映像格子系统中存在着多个共存的吸引子. 因此, 其冻结化图案的结构和分布敏感地依赖于格点动力学变量初始值的选取. 感兴趣地是, 即使当单映像处于混沌状态时, 格点间的耦合仍能将系统调制到规则的运动状态, 这种特征对于混沌控制具有重要的利用价值. 上述丰富动力学行为的出现是由于单映像中不连续性和不可逆性相互作用的结果.     

Lorenz系统驱动声光双稳时空混沌系统并行同步的研究

研究了一个时间混沌系统驱动多个时空混沌系统的并行同步问题.以单模激光Lorenz系统和一维耦合映像格子为例,在单模激光Lorenz系统中提取一个混沌序列,通过与一维耦合映像格子中的状态变量耦合使单模激光Lorenz系统和多个同结构一维耦合映像格子同时达到广义同步,并且多个一维耦合映像格子之间实现完全并行同步.通过计算条件Lyapunov指数,可以得到并行同步所需反馈系数的取值范围.数值模拟证明了此方法的可行性和有效性.     

一个全局耦合不连续映像格子中的奇异态

文章研究了一类由既不可逆又不连续映像构成的全局耦合映像格子系统中的奇异态行为,计算了系统的同步序参量和空间振幅变化图.结果表明,在某些特定的参数区间内,耦合映像格子系统会出现奇异态或团簇态,并且敏感地依赖于耦合强度的选择.上述丰富的动力学现象是由于单映像中不连续、不可逆性以及空间耦合相互作用的结果.通过数值模拟找到了奇异态或团簇态出现的特定参数区域.     

基于条件熵长江三角洲温度的非线性动力学特征分析

通过粗粒化方法得到符号序列，如果两个符号序列的条件熵在相对位移为零时达到最小值，那么这两个时间序列可能属于同一个动力学系统.进一步可以判断两个时间序列之间的耦合强度并提取出两个动力学耦合信号之间的内在滞后关系.本文用条件熵算法分析了长江三角洲地区上海、南通、常州、南京和杭州的逐日气温资料，判断这些地区的温度是否属于同一个动力学系统以及它们之间的动力学耦合关系，并提取出它们之间的滞后信息. 关键词： 粗粒化 条件熵 动力学耦合 滞后时间     

Analysis of convergence for initial condition estimation of coupled map lattices based on symbolic dynamics

A novel approach to the inverse problem of diffusively coupled map lattices is systematically investigated by utilizing the symbolic vector dynamics.The relationship between the performance of initial condition estimation and the structural feature of dynamical system is proved theoretically.It is found that any point in a spatiotemporal coupled system is not necessary to converge to its initial value with respect to sufficient backward iteration,which is directly relevant to the coupling strength and local mapping function.When the convergence is met,the error bound in estimating the initial condition is proposed in a noiseless environment,which is determined by the dimension of attractors and metric entropy of the system.Simulation results further confirm the theoretic analysis,and prove that the presented method provides the important theory and experimental results for better analysing and characterizing the spatiotemporal complex behaviours in an actual system.     

Estimation of chaotic coupled map lattices using symbolic vector dynamics

In [K. Wang, W.J. Pei, Z.Y. He, Y.M. Cheung, Phys. Lett. A 367 (2007) 316], an original symbolic vector dynamics based method has been proposed for initial condition estimation in additive white Gaussian noisy environment. The estimation precision of this estimation method is determined by symbolic errors of the symbolic vector sequence gotten by symbolizing the received signal. This Letter further develops the symbolic vector dynamical estimation method. We correct symbolic errors with backward vector and the estimated values by using different symbols, and thus the estimation precision can be improved. Both theoretical and experimental results show that this algorithm enables us to recover initial condition of coupled map lattice exactly in both noisy and noise free cases. Therefore, we provide novel analytical techniques for understanding turbulences in coupled map lattice.     

A method of estimating initial conditions of coupled maplattices based on time-varying symbolic dynamics

A novel computationally efficient algorithm in terms of the time-varying symbolic dynamic method is proposed to estimate the unknown initial conditions of coupled map lattices (CMLs). The presented method combines symbolic dynamics with time-varying control parameters to develop a time-varying scheme for estimating the initial condition of multi-dimensional spatiotemporal chaotic signals. The performances of the presented time-varying estimator in both noiseless and noisy environments are analysed and compared with the common time-invariant estimator. Simulations are carried out and the obtained results show that the proposed method provides an efficient estimation of the initial condition of each lattice in the coupled system. The algorithm cannot yield an asymptotically unbiased estimation due to the effect of the coupling term, but the estimation with the time-varying algorithm is closer to the Cramer--Rao lower bound (CRLB) than that with the time-invariant estimation method, especially at high signal-to-noise ratios (SNRs).     

Effect of noise on coupled chaotic systems

The effect of noise in inducing order on various chaotically evolving systems is reviewed, with special emphasis on systems consisting of coupled chaotic elements. In many situations it is observed that the uncoupled elements when driven by identical noise, show synchronization phenomena where chaotic trajectories exponentially converge towards a single noisy trajectory, independent of the initial conditions. In a random neural network, with infinite range coupling, chaos is suppressed due to noise and the system evolves towards a fixed point. Spatiotemporal stochastic resonance phenomenon has been observed in a square array of coupled threshold devices where a temporal characteristic of the system resonates at a given noise strength. In a chaotically evolving coupled map lattice with the logistic map as local dynamics and driven by identical noise at each site, we report that the number ofstructures (a structure is a group of neighbouring lattice sites for values of the variable follow which the certain predefined pattern) follows a power-law decay with the length of the structure. An interesting phenomenon, which we callstochastic coherence, is also reported in which the abundance and lifetimes of these structures show characteristic peaks at some intermediate noise strength.     

A method of recovering the initial vectors of globally coupled map lattices based on symbolic dynamics

Based on symbolic dynamics, a novel computationally efficient algorithm is proposed to estimate the unknown initial vectors of globally coupled map lattices (CMLs). It is proved that not all inverse chaotic mapping functions are satisfied for contraction mapping. It is found that the values in phase space do not always converge on their initial values with respect to sufficient backward iteration of the symbolic vectors in terms of global convergence or divergence (CD). Both CD property and the coupling strength are directly related to the mapping function of the existing CML. Furthermore, the CD properties of Logistic, Bernoulli, and Tent chaotic mapping functions are investigated and compared. Various simulation results and the performances of the initial vector estimation with different signal-to-noise ratios (SNRs) are also provided to confirm the proposed algorithm. Finally, based on the spatiotemporal chaotic characteristics of the CML, the conditions of estimating the initial vectors using symbolic dynamics are discussed. The presented method provides both theoretical and experimental results for better understanding and characterizing the behaviours of spatiotemporal chaotic systems.     

时空混沌的单向耦合同步

以耦合映象格子模型为例,提出利用单向耦合驱动时空混沌的同步方案,并进行了数值分析.结果表明,适当地选择耦合驱动强度因子和均衡系数,两个时空混沌系统可以达到准确同步.通过计算最大条件Lyapunov指数,给出了可实现时空混沌同步的最小耦合强度以及最小耦合强度与系统参数之间的关系曲线.数值模拟还证明,此方法工作鲁棒 关键词： 时空混沌 同步 单向耦合 最大条件Lyapunov指数 数值模拟     

弱耦合映射系统在周期窗口内的行为

通过解析讨论及数值计算的验证,发现弱耦合映射系统的周期窗口只存在于耦合强度极小的范围内(对于3周期窗口大约为10^-3),这个范围可以定义为周期窗口的深度。在周期窗口内耦合映射的行为可以通过讨论少数几个模(相对简单的耦合三映射,实质是一维映射)而确定。耦合映射的第一Lyapunov指数随耦合强度增大的变化曲线呈锯齿形状。 关键词：     

Scaling Region in Desynchronous Coupled Chaotic Maps

The largest Lyapunov exponent and the Lyapunov spectrum of a coupled map lattice are studied when the system state is desynchronous chaos. In the large system size limit a scaling region is found in the parameter space where the largest Lyapunov exponent is independent of the system size and the coupling strength. Some scaling relation between the Lyapunov spectrum distributions for different coupling strengths is found when the coupling strengths are taken in the scaling parameter region. The existence of the scaling domain and the scaling relation of Lyapunov spectra there are heuristically explained.     

Scaling Region in Desynchronous Coupled Chaotic Maps

The largest Lyapunov exponent and the Lyapunov spectrum of a coupled map lattice are studied when the system state is desynchronous chaos. In the large system size limit a scaling region is found in the parameter space where the largest Lyapunov exponent is independent of the system size and the coupling strength. Some scaling relation between the Lyapunov spectrum distributions for different coupling strengths is found when the coupling strengths are taken in the scaling parameter region. The existence of the scaling domain and the scaling relation of Lyapunov spectra there are heuristically explained.