混沌时序相空间重构参数确定的信息论方法

根据信息论基本原理，研究了混沌时间序列相空间重构参数延迟时间和嵌入维数的选取.提出了用符号分析的方法计算互信息函数，确定出延迟时间，在此基础上，提出了一种估计嵌入维数的信息论方法，即根据重构向量条件熵随向量维数的变化关系来确定嵌入维数，通过对几种典型混沌动力学系统的数值验证，结果表明该方法能够确定出合适的相空间重构嵌入维数. 关键词： 混沌 相空间重构 互信息 条件熵 符号分析     

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     

A quantum deformation of invariants of binary forms

The modern representation theory has its roots in the classical theory of invariants of binary forms of Caley, Silvester, Clebsch, Gordan, Capelli etc. We use the theory of the quantum group U _q(sl(2, IR) in order to develop a quantum theory of invariants. Higher binary forms are introduced on the basis of braided algebras. We define quantised invariants and give basic examples. We show that the symbolic method of Clebsch and Gordan works also in the quantised case. We calculate the quantised discriminant of the quadratic form, the quantised catalecticant of the quartic form and further invariants without a classical analogon.     

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.     

Symbolic dynamics of one-dimensional maps: Entropies,finite precision,and noise

In the study of nonlinear physical systems, one encounters apparently random or chaotic behavior, although the systems may be completely deterministic. Applying techniques from symbolic dynamics to maps of the interval, we compute two measures of chaotic behavior commonly employed in dynamical systems theory: the topological and metric entropies. For the quadratic logistic equation, we find that the metric entropy converges very slowly in comparison to maps which are strictly hyperbolic. The effects of finite precision arithmetric and external noise on chaotic behavior are characterized with the symbolic dynamics entropies. Finally, we discuss the relationship of these measures of chaos to algorithmic complexity, and use algorithmic information theory as a framework to discuss the construction of models for chaotic dynamics.     

累积放电模型及其符号动力学研究

基于累积释放模型提出了一种累积放电模型.相比于累积释放模型, 累积放电模型无须变化的阈值调制, 即可出现多种状态, 例如混沌态、锁频等. 利用符号动力学对其进行研究, 发现在一定的参数条件下, 模型的输出符号序列可以被用于监测模型参数的变化, 而且与神经系统的测量相似, 都具有很高的分辨率. 计算机仿真和电路实验得到的结果也验证了上述说法. 电路实验结果显示模型的输出符号序列对输入频率的分辨率最高可以达到0.05 Hz, 对电流幅值的分辨率可达到1 μA, 并且都具有很大的动态范围. 关键词： 符号动力学 混沌 累积释放模型 非线性电路     

DC-DC变换器的符号时间序列描述及模块熵分析

本文提出了一种采用符号时间序列和熵理论分析DC-DC变换器非线性行为的方法.该方法首先用离散时间序列描述非线性连续系统,然后将其转换为由简单字符构成的符号序列,再用信息学方法计算出该符号序列的模块熵,从而得到一种新的可量化的非线性动力学行为统计指标.文中以一阶电压反馈DCM和二阶电流反馈CCM Boost变换器为例进行研究.研究结果表明,模块熵这种粗粒化的统计分析方法,能够量化DC-DC变换器的倍周期分岔和混沌行为,且能够准确地确定混沌行为的发生,是一种尚未在DC-DC变换器中提出的简单、实用的分析方法. 关键词： 符号时间序列 符号动力学 模块熵 Lyapunov指数     

基于等概率符号分析方法计算互信息确定延迟时间

用互信息函数确定混沌时间序列相空间重构最佳延迟时间.针对常规符号分析方法计算互信息准确度不高的缺陷,提出等概率符号分析方法计算互信息,即对时间序列按值域大小重排列,再对重排后的序列进行等概率分割,分割的组数由分组经验公式确定,然后取每组的边界值组成符号分析方法的临界点集合进行计算.通过对Lorenz方程和强迫Brusselator振子进行仿真实验,得到的最佳延时与Fraser等概率分格子法得到的结果一致,而算法上更容易实现,证明方法有效.     

The order of chaos on a Bianchi-IX cosmological model

The purpose of this paper is to analyze the chaotic behavior that can arise on a type-IX cosmological model using methods from dynamic systems theory and symbolic dynamics. Specifically, instead of the Belinski-Khalatnikov-Lifschitz model, we use the iterates of a monotonously increasing map of the circle with a discontinuity, and for the Hamiltonean dynamics of Misner's Mixmaster model we introduce the iterates of a noninvertible map. An equivalence between these two models can easily be brought upon by translating them in symbolic-dynamical terms. The resulting symbolic orbits can be inserted in an ordered tree structure set, and so we can present an effective counting and referentation of all period orbits.     

New periodic wave solutions via Exp-function method

The Exp-function method with the aid of symbolic computational system is used to obtain the generalized solitary solutions and periodic solutions for nonlinear evolution equations arising in mathematical physics, namely, nonlinear partial differential (BBMB) equation, generalized RLW equation and generalized shallow water wave equation. It is shown that the Exp-function method, with the help of symbolic computation, provides a powerful mathematical tool for solving other nonlinear evolution equations arising in mathematical physics.     

用符号分析法显示时空混沌信号之间的相互关系

基于耦合映射格子模型, 用符号分析法研究了时空混沌信号的相互关系. 数值计算结果表明, 两个直接耦合的格子之间或两个未直接耦合但邻近的格子之间的条件熵存在一个尖锐的极小值, 而两个距离比较远的格子之间的条件熵则没有尖锐的极小值. 因此, 耦合映射格子系统产生的时空混沌信号之间的相互关系可以通过符号分析的方法显示出来.     

双耳幅值差确定声源方向的神经信息处理机理研究

神经信息系统实质上是定量系统, 应引起足够重视. 关于神经系统的定量研究方面的报道比较少见. 这一问题将会影响进一步的研究, 如双耳声音定向. 双耳定向是定量测量, 用定性分析的方法无法满足要求. 已有的生理实验发现声音输入信号强度与听觉神经的输出频率存在单调递增关系, 所以本文中声音强度的变化被简化成神经脉冲频率的变化. 本文基于圆映射和符号动力学原理, 建立了神经回路定量模型, 模型中对同侧输入回路采用兴奋性耦合, 对侧输入回路采用抑制性耦合, 并考虑神经元间突触连接的量子释放特征, 采用化学耦合模型实现连接, 用耦合系数表示神经元间的耦合程度. 采用Hodgkin-Huxley模型仿真研究听觉神经回路的输入/输出脉冲序列关系. 在已经仿真过的参数范围, 模型在输入信号变化与输出脉冲频率变化间存在单调递增/递减的关系. 对于单输入单输出的神经元, 采用符号动力学方法进行符号化; 对于多输入单输出的神经元, 采用分析各输出脉冲的产生时间, 判断其变化位置, 从神经脉冲序列中得到对应的两耳声音幅值差变化, 以此定位声源. 随着输出脉冲数的增加, 符号序列的长度增加, 符号序列对输入信号变化敏感, 能够得到较高的测量精度. 仿真结果表明这个模型是定量的, 神经脉冲序列能够区分信号的大小.     

异垂盆草甙元晶体结构的测定(Ⅱ)——用分量关系式复原对映双解E图

以附加记号法测定异垂盆草甙元的晶体结构时,出现了相位退化问题,由此得到同时混含两个对映体的E图,应用分量关系式成功地将这样的E图复原为只含一个对映体的E图。这一成功表明:使用附加记号法测定非中心对称的晶体结构,当出现相位退化时无需迴避,这就提高了附加记号法的使用效力。     

Bloch-Redfield-Wangsness theory engine implementation using symbolic processing software

We describe a general method for the automated symbolic processing of Bloch-Redfield-Wangsness relaxation theory equations for liquid-phase spin dynamics in the algebraically challenging case of rotationally modulated interactions. The processing typically takes no more than a few seconds (on a contemporary single-processor workstation) and yields relaxation rate expressions that are completely general with respect to the spectral density functions, relative orientations, and magnitudes of the interaction tensors, with all cross-correlations accounted for. The algorithm easily deals with fully rhombic interaction tensors, and is able, with little if any modification, to treat a large variety of the relaxation mechanisms encountered in NMR, EPR, and spin dynamics in general.     

Estimating optimal partitions for stochastic complex systems

Partitions provide simple symbolic representations for complex systems. For a deterministic system, a generating partition establishes one-to-one correspondence between an orbit and the infinite symbolic sequence generated by the partition. For a stochastic system, however, a generating partition does not exist. In this paper, we propose a method to obtain a partition that best specifies the locations of points for a time series generated from a stochastic system by using the corresponding symbolic sequence under a constraint of an information rate. When the length of the substrings is limited with a finite length, the method coincides with that for estimating a generating partition from a time series generated from a deterministic system. The two real datasets analyzed in Kennel and Buhl, Phys. Rev. Lett. 91, 084102 (2003), are reanalyzed with the proposed method to understand their underlying dynamics intuitively.     

Intentional systems: Review of neurodynamics, modeling, and robotics implementation

We present an intentional neurodynamic theory for higher cognition and intelligence. This theory provides a unifying framework for integrating symbolic and subsymbolic methods as complementary aspects of human intelligence. Top-down symbolic approaches benefit from the vast experience with logical reasoning and with high-level knowledge processing in humans. Connectionist methods use bottom-up approach to generate intelligent behavior by mimicking subsymbolic aspects of the operation of brains and nervous systems. Neurophysiological correlates of intentionality and cognition include sequences of oscillatory patterns of mesoscopic neural activity. Oscillatory patterns are viewed as intermittent representations of generalized symbol systems, with which brains compute. These dynamical symbols are not rigid but flexible. They disappear soon after they emerged through spatio-temporal phase transitions. Intentional neurodynamics provides a solution to the notoriously difficult symbol grounding problem. Some examples of implementations of the corresponding dynamic principles are described in this review.     

Multiple rogue wave solutions for (2+1)-dimensional Boussinesq equation

In this paper, a modified symbolic computation approach is proposed. The multiple rogue wave solutions of a generalized (2+1)-dimensional Boussinesq equation are obtained by using the modified symbolic computation approach. Dynamics features of these obtained multiple rogue wave solutions are displayed in 3D and contour plots. Compared with the original symbolic computation approach, our method does not need to find Hirota bilinear form of nonlinear system.     

基于符号动力学的认知事件相关电位的复杂度分析

引入了符号动力学方法分析认知事件相关电位(ERP)的复杂度.以混合模型生成的随机时间序列为例,对近似熵和符号熵作了比较.应用符号熵分析了Oddball范式中不同任务条件(靶刺激和非靶刺激)下的ERP的复杂度.研究发现,额区、中央区和顶区的ERP复杂度在刺激呈现后的任务加工时间段内显著减小(非靶刺激和靶刺激分别在刺激呈现后200—300和400—500ms),而且靶刺激ERP复杂度大约在P300成分的峰值时刻达到最小值,在响应之后逐渐回升.这表明基于符号动力学的复杂度分析能够反映认知任务加工的时间过程,并且 关键词： 事件相关电位 符号动力学 熵     

An efficient block variant of robust structured multifrontal factorization method

Based on the two-dimensional three-temperature （2D3T） radiation diffusion equations and its discrete system, using the block diagonal structure of the three-temperature matrix, the reordering and symbolic decomposition parts of the RSMF method are replaced with corresponding block operation in order to improve the solution efficiency. We call this block form method block RSMF （in brief, BRSMF） method. The new BRSMF method not only makes the reordering and symbolic decomposition become more effective, but also keeps the cost of numerical factorization from increasing and ensures the precision of solution very well. The theoretical analysis of the computation complexity about the new BRSMF method shows that the solution efficiency about the BRSMF method is higher than the original RSMF method. The numerical experiments also show that the new BRSMF method is more effective than the original RSMF method.     

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