基于改进的符号转移熵的心脑电信号耦合研究

试图探究动力系统中的耦合关系一直以来都是国内外众多学者关注的热点,传统的时间序列符号化分析方法会使研究结果受序列非平稳性的严重影响,本文在原有转移熵的研究基础上,应用粗粒化提取,经过理论与实验的分析,发现心脑电信号耦合研究中的转移熵值在不同提取情况下对应不同的分布趋势,并选择效果最好的信号数据提取方法用在其后的应用分析中. 此外,对时间序列符号化方法提出改进,采用动态的自适应分割方法. 实验结果表明,无论清醒期还是睡眠期,改进的符号转移熵算法观测分析到的心脑电信号耦合作用更显著,能更好的捕捉到信号中的动态信息、系统动力学复杂性的改变,更利于医学临床实践应用中的检测,在分析非平稳的时间序列上具有更好的效果. 关键词： 心脑电信号 粗粒化 符号转移熵 基本尺度     

基于条件熵扩维的多变量混沌时间序列相空间重构

提出一种多变量混沌时间序列相空间重构的条件熵扩维方法.首先使用互信息法求解每个变量的时间延迟,其次按条件熵最大原则逐步扩展相空间的嵌入维数,使得重构坐标从低维到高维的转换保持较强的独立性,最终的重构相空间具有较低的冗余度,为多变量时间序列的预测构造了有效的模型输入向量.通过对几个经典多变量混沌时间序列进行数值实验,结果表明该方法比单变量预测和已有多变量预测方法具有更好的预测效果,说明了该重构方法的有效性. 关键词： 多变量混沌时间序列 相空间重构 条件熵 神经网络预测     

基于Gay-Berne势能模型的粗粒化动力学模拟研究正丁醇的玻璃态相变

通过基于Gay-Berne势能模型的粗粒化动力学模拟,研究液态正丁醇体系的冷却过程. 采用密度泛函计算,拟合出适合正丁醇体系的GB势能参数. 体系的密度、平均势能等性质随温度的降低(由290 K降至50 K,间隔为10 K)发生特殊变化,即体系发生玻璃态相变,相变温度为T_g=120±10 K,与实验值110±1 K符合很好.     

基于符号动力学的开关变换器时间不可逆性分析

本文提出了一种采用符号动力学和相对熵理论分析开关变换器非线性特性的新方法.根据迭代映射描述的开关变换器非线性系统得到离散数值序列,基于拓扑共轭理论将其转化为符号序列,通过前向序列和后向序列概率计算该符号序列的相对熵.文中以一阶电压反馈DCM Boost变换器为例,研究结果表明,开关变换器存在时间不可逆性,相对熵数值能够量化开关变换器处于混沌状态时离开平衡点的距离,从而得到一种新的可量化的开关变换器非线性动力学行为指标.     

各向异性光子晶体中熵压缩动力学行为

本文详细分析了各向异性光子晶体环境中量子弱测量和测量反转对原子熵压缩的影响,得到一些重要结论。研究发现,量子比特和光子晶体带隙边缘频率之间的失谐量δ以及量子弱测量和测量反转强度对熵压缩起着重要作用,通过调节它们,可以获得更好的熵压缩。     

随机反应扩散格气模型上钙动力学的粗粒化模拟

发展了一种基于随机格气模型的粗粒化方法,该方法能有效模拟内质网表面钙动力学信息. 首先将相邻的微观节点合并成粗粒化节点,再根据局域平均场近似推导出粗粒化反应速率,然后执行粗粒化动力学蒙特卡洛模拟. 发现粗粒化动力学蒙特卡洛模拟结果和微观模拟结果非常吻合. 有趣的是,存在一个最佳的粗粒化比m,使得粗粒化模拟与微观模拟的相变点偏差最小. 固定m,发现临界点随体系尺度增加而单调增加,而且相变点的偏差与体系尺度存在一个标度关系.此外,该粗粒化方法大大地加快了蒙特卡洛模拟速率,并且与微观模拟直接相关. 该方法可以广泛用来研究体系尺度效应,而节省大量计算时间.     

两相流流型多尺度熵及动力学特性分析

研究了几种典型非线性时间序列的多尺度熵特征,在此基础上分析了由插入式阵列电导传感器采集的144种流动条件下的垂直上升气液两相流电导波动信号.研究结果表明：利用小尺度下样本熵的变化速率特征可以分辨三种典型流型（泡状流、段塞流、混状流）,而大尺度下样本熵的波动特征可以反映各种流型的动力学特性.泡状流随机可变特性表现为大尺度下样本熵的高值及振荡特征;段塞流气塞与液塞的间歇性运动表现为大尺度下样本熵的低值及平稳性;混状流极不稳定的振荡运动特性表现为介于泡状流及段塞流之间的熵值特点,并在更大尺度时熵值逐渐接近泡状流 关键词： 样本熵 多尺度熵 气液两相流 动力学特性     

Kerr效应对非线性Jaynes-Cummings模型场熵和缠结的影响

Phoenix和Knight提出的量子熵理论,用量子熵作为缠结程度的量度,研究了附加克尔介质依赖强度耦合Jaynes-Cummings模型场熵演化的动力学特性和原子-场的缠结特性,详细地讨论了克尔效应及初始相干光场的强弱对场熵演化特性和原子-场缠结特性的影响,并与原子反转特性相比较.结果表明:在初始相干光场较弱时(n=10),克尔介质的非线性相互作用破坏了场熵演化的周期性,原子-场不再周期消缠结.但在初始相干光场较强时(n=50),克尔介质非线性相互作用只是使场熵演化的周期性减弱,场熵的演化仍近似地有周期性,原子-场仍周期消缠结,克尔效应越强,周期越小.当克尔介质与光场强耦合相互作用时(χ/g=5),原子-场持续消缠结.     

负值量子条件熵与双量子系统一类混合态纠缠量度

运用负值量子条件熵研究了双量子系统一类混合态的纠缠量度.给出了负值量子条件作为条件熵纠缠度的定义，证明了条件熵纠缠满足作为2×2系统一类混合纠缠态量度的四个基本条件.当双量子系统处于纯态时，条件熵纠缠度即为部分熵纠缠度.应用条件熵纠缠度研究了真空腔场中两全同二能级原子之间纯态和一类混合态纠缠的时间演化，比较了相同条件下两全同原子系统concurrence纠缠度的时间演化.结果表明，两纠缠度演化规律完全一致，验证了负值量子条件熵可以作为双量子系统纯态和一类混合态的纠缠量度. 关键词： 双量子系统 负值量子条件熵 条件熵纠缠度 混合态纠缠度     

利用排列熵检测近40年华北地区气温突变的研究

运用一种新的动力学突变检测方法——排列熵(permutation entropy，PE)算法，计算并分析了中国华北地区52个站点1960年—2000年逐日平均气温资料的排列熵演化情况，发现中国华北地区气温在20世纪70年代中期、80年代初均发生了较大突变；进一步用经验模态分解(empirical mode decomposition，EMD)方法对排列熵序列进行逐级平稳化处理，结果发现这一地区的气温突变与准10年这一年代际时间尺度的周期变率密切相关，其原因与太阳黑子活动有着密切联系. 关键词： 华北 突变 排列熵算法 经验模态分解     

一种识别混沌时间序列动力学异同性的方法

定义了两个新的统计量，分别记为Q和R，Q称为动力学自相关因子指数，R称为动力学互相关 因子指数.用Q和R对不同时间序列的动力学“距离”或同一时间序列中不同区段（窗口）的 动力学“距离”进行估算，可以鉴别这些时间序列的动力学属性或它们内在的动力学结构层 次以及复杂性.一些典型实例检验表明，这种方法是有效的. 关键词： 混沌时间序列 动力学自相关因子指数 动力学互相关因子指数     

Detecting dynamical complexity changes in time series using the base-scale entropy

Timely detection of dynamical complexity changes in natural and man-made systems has deep scientific and practical meanings. We introduce a complexity measure for time series： the base-scale entropy. The definition directly applies to arbitrary real-word data. We illustrate our method on a practical speech signal and in a theoretical chaotic system. The results show that the simple and easily calculated measure of base-scale entropy can be effectively used to detect qualitative and quantitative dynamical changes.     

Fine-grained permutation entropy as a measure of natural complexity for time series

In a recent paper [2002 Phys. Rev. Lett. 88 174102], Bandt and Pompe propose permutation entropy (PE) as a natural complexity measure for arbitrary time series which may be stationary or nonstationary, deterministic or stochastic. Their method is based on a comparison of neighbouring values. This paper further develops PE, and proposes the concept of fine-grained PE (FGPE) defined by the order pattern and magnitude of the difference between neighbouring values. This measure excludes the case where vectors with a distinct appearance are mistakenly mapped onto the same permutation type, and consequently FGPE becomes more sensitive to the dynamical change of time series than does PE, according to our simulation and experimental results.     

Evaluating the dynamical coupling between spatiotemporally chaotic signals via an information theory approach

An information-theoretic measure is introduced for evaluating the dynamical coupling of spatiotemporally chaotic signals produced by extended systems. The measure of the one-way coupled map lattices and the one-dimensional, homogeneous, diffusively coupled map lattices is computed with the symbolic analysis method. The numerical results show that the information measure is applicable to determining the dynamical coupling between two directly coupled or indirectly coupled chaotic signals.     

Upper bound for the time derivative of entropy for a stochastic dynamical system with double singularities driven by non-Gaussian noise

A stochastic dynamical system with double singularities driven by non-Gaussian noise is investigated. The Fokker--Plank equation of the system is obtained through the path-integral approach and the method of transformation. Based on the definition of Shannon's information entropy and the Schwartz inequality principle, the upper bound for the time derivative of entropy is calculated both in the absence and in the presence of non-equilibrium constraint. The present calculations can be used to interpret the effects of the system dissipative parameter, the system singularity strength parameter, the noise correlation time and the noise deviation parameter on the upper bound.     

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     

Global dynamical analysis of vibrational manifolds of HOCl and HOBr under anharmonicity and Fermi resonance: the dynamical potential approach

The vibrational dynamics of HOCl and HOBr between bending and OCl/OBr stretching coordinates with anharmonicity and Fermi coupling is studied with the classical dynamical potential approach. The quantal vibrational dynamics is mostly mapped out by the classical nonlinear variables such as fixed points, except for the state energies, which are quantized. This approach is global in the sense that the focus is on a set of levels instead of individual ones. The dynamics of HOBr is demonstrated to be less complicated. The localized modes along the OCl/OBr stretching coordinates are also shown to have O--Br bonds more prone to dissociation.     

Global dynamical analysis of vibrational manifolds of HOCl and HOBr under anharmonicity and Fermi resonance:the dynamical potential approach

The vibrational dynamics of HOCl and HOBr between bending and OCl/OBr stretching coordinates with anharmonicity and Fermi coupling is studied with the classical dynamical potential approach. The quantal vibrational dynamics is mostly mapped out by the classical nonlinear variables such as fixed points, except for the state energies, which are quantized. This approach is global in the sense that the focus is on a set of levels instead of individual ones. The dynamics of HOBr is demonstrated to be less complicated. The localized modes along the OCl/OBr stretching coordinates are also shown to have O-Br bonds more prone to dissociation.     

Wasserstein distances in the analysis of time series and dynamical systems

A new approach based on Wasserstein distances, which are numerical costs of an optimal transportation problem, allows us to analyze nonlinear phenomena in a robust manner. The long-term behavior is reconstructed from time series, resulting in a probability distribution over phase space. Each pair of probability distributions is then assigned a numerical distance that quantifies the differences in their dynamical properties. From the totality of all these distances a low-dimensional representation in a Euclidean space is derived, in which the time series can be classified and statistically analyzed. This representation shows the functional relationships between the dynamical systems under study. It allows us to assess synchronization properties and also offers a new way of numerical bifurcation analysis.The statistical techniques for this distance-based analysis of dynamical systems are presented, filling a gap in the literature, and their application is discussed in a few examples of datasets arising in physiology and neuroscience, and in the well-known Hénon system.