A brief description to different multi-fractal behaviors of daily wind speed records over China

Scaling behaviors of the long daily wind speed records of four selected weather stations over China were analyzed by using Multi-Fractal Detrended Fluctuation Analysis (MF-DFA). The results indicated that all these four stations are characterized by long-range power-law correlations, but MF-DFA results showed non-universal multi-fractal behaviors over China. We fitted generalized Hurst exponent h(q) via a modified generalized binomial multiplicative cascade model, and different widths of the multi-fractal spectrum are estimated.     

Multi-fractal analysis of highway traffic data

The purpose of the present study is to investigate the presence of multi-fractal behaviours in the traffic time series not only by statistical approaches but also by geometrical approaches. The pointwise H\"{o} lder exponent of a function is calculated by developing an algorithm for the numerical evaluation of H\"{o} lder exponent of time series. The traffic time series observed on the Beijing Yuquanying highway are analysed. The results from all these methods indicate that the traffic data exhibit the multi-fractal behaviour.     

An improved computing method for the image edge detection

The framework of detecting the image edge based on the sub-pixel multi-fractal measure (SPMM) is presented. The measure is defined, which gives the sub-pixel local distribution of the image gradient. The more precise singularity exponent of every pixel can be obtained by performing the SPMM analysis on the image. Using the singularity exponents and the multi-fractal spectrum of the image, the image can be segmented into a series of sets with different singularity exponents, thus the image edge can be detected automatically and easily. The simulation results show that the SPMM has higher quality factor in the image edge detection.     

基于多分辨分析的高炉铁水含硅量波动多重分形辨识

以包钢6号高炉、邯钢7号高炉和莱钢1号高炉在线采集的铁水含硅量(［Si］)的时间序列为样本, 利用多分辨分析剔除样本的长期趋势,对样本保留的波动趋势进行多重分形特征辨识. 通过计算广义Hurst指数、尺度函数、多重分形谱, 全面、细致量化了序列的局部及不同层次的波动奇异性. 计算结果表明: 去除长期趋势后, 三座高炉［Si］序列的波动呈现显著多重分形特征, 这样的波动过程仅用单一的Hurst指数或box维数来描述是不够的. 关键词： 多分辨分析 铁水含硅量 波动 多重分形     

东亚区域大气长程相关性

运用去趋势涨落分析方法分别研究NCEP/NCAR再分析资料中的高度场和温度场,揭示了东亚区域高度场和温度场的标度指数分布特征.结果表明高度场和温度场都具有长程相关性,且二者空间分布特征总体匹配.对同一层格点资料而言,低纬度地区标度指数较大,长程相关性较好;中高纬度地区标度指数较小,长程相关性较差,呈现比较明显的纬向分布特征.不同层格点资料的标度指数分布有所区别,具体表现为高度场资料随层数的增加,其平均标度指数值呈增长趋势且纬向分布特征更为明显;在高度场中下层青藏高原地区标度指数明显大于同纬度其他区域.温度场资料随层数的增加平均标度指数先减小再增大,也具有一定的纬向分布特征.总体而言,高度场长程相关性的标度指数值要高于温度场.分季节研究表明,高度场和温度场也具有较好的长程相关性,冬季标度指数高于其他季节,为利用冬季信息制作夏季汛期预报提供了一定的理论依据. 关键词： 高度场 温度场 长程相关性 去趋势涨落分析     

菲波纳契准周期超结构光纤光栅

采用相位掩模板扫描法,在单模光敏光纤中制备了中心波长为1 541.86 nm,菲波纳契序数为0～9的准周期超结构光栅.通过模拟引入相移过程中纤芯折射率的改变对制作参量进行了优化.传输矩阵分析与实验结果均表明,该超结构光纤光栅的透射谱呈现分形结构,在中心波长附近有六循环和自相似特性.所制备超结构光栅可作为C波段分形结构滤波器件在光通信和全光集成领域得到应用.     

The largest Lyapunov exponent of chaotic dynamical system in scale space and its application

The largest Lyapunov exponent is an important invariant of detecting and characterizing chaos produced from a dynamical system. We have found analytically that the largest Lyapunov exponent of the small-scale wavelet transform modulus of a dynamical system is the same as the system's largest Lyapunov exponent, both discrete map and continuous chaotic attractor with one or two positive Lyapunov exponents. This property has been used to estimate the largest Lyapunov exponent of chaotic time series with several kinds of strong additive noise.     

Multifractal moving average analysis and test of multifractal model with tuned correlations

We address two common major problems in the study of time series characterizing fluctuations in complex systems: multifractal analysis and multifractal modeling. Specifically, we introduce a multi-fractal centered moving average (MF-CMA) analysis, which is computationally easier but equivalently performing compared with the well-established multi-fractal detrended fluctuation analysis (MF-DFA) with linear detrending. In addition, we study in detail a generalized binomial multi-fractal model (GB-MFM) to conveniently and reliably generate multifractal surrogate data with arbitrary singularity strengths and arbitrary long-term persistence. We use the data generated by this model as well as realistic, by construction monofractal data series with crossovers and trends to test and compare the multifractal analysis methods and discuss finite-size effects as well as limitations due to spurious multifractality.     

近50年中国降水及温度变化在干旱形成中的影响

根据中国气象局1958—2007年194站的温度、降水和Palmer旱涝指数（Palmer Drought Severity Index, PDSI）均一化数据库,构建统计模型量化了温度和降水变化在干旱形成中所占的比重,尤其讨论了中国8个气候区域温度和降水变化在干旱成因中的特征.受全球增温趋势的影响,未来中国北方地区的干旱化趋势仍将继续.未来五年内干旱发生概率较大的地区主要分布在中国华北,且有持续向南扩张的趋势,一直延伸到江淮地区.在全球变暖的背景下,降水减少仍然是中国东部干旱形成的主要因素.相对于南方地 关键词： 降水 全球变暖 干旱     

Empirical behavior of a world stock index from intra-day to monthly time scales

Most of the papers that study the distributional and fractal properties of financial instruments focus on stock prices or foreign exchange rates. This typically leads to mixed results concerning the distributions of log-returns and some multi-fractal properties of exchange rates, stock prices, and regional indices. This paper uses a well diversified world stock index as the central object of analysis. Such index approximates the growth optimal portfolio, which is demonstrated under the benchmark approach, it is the ideal reference unit for studying basic securities. When denominating this world index in units of a given currency, one measures the movements of the currency against the entire market. This provides a least disturbed observation of the currency dynamics. In this manner, one can expect to disentangle, e.g., the superposition of the two currencies involved in an exchange rate. This benchmark approach to the empirical analysis of financial data allows us to establish remarkable stylized facts. Most important is the observation that the repeatedly documented multi-fractal appearance of financial time series is very weak and much less pronounced than the deviation of the mono-scaling properties from Brownian-motion type scaling. The generalized Hurst exponent H(2) assumes typical values between 0.55 and 0.6. Accordingly, autocorrelations of log-returns decay according to a power law, and the quadratic variation vanishes when going to vanishing observation time step size. Furthermore, one can identify the Student t distribution as the log-return distribution of a well-diversified world stock index for long time horizons when a long enough data series is used for estimation. The study of dependence properties, finally, reveals that jumps at daily horizon originate primarily in the stock market while at 5min horizon they originate in the foreign exchange market. The principal message of the empirical analysis is that there is evidence that a diffusion model without multi-scaling could reasonably well model the dynamics of a broadly diversified world stock index.     

菲波纳契准周期超结构光纤光栅

采用相位掩模板扫描法,在单模光敏光纤中制备了中心波长为1 541.86 nm,菲波纳契序数为0~9的准周期超结构光栅.通过模拟引入相移过程中纤芯折射率的改变对制作参量进行了优化.传输矩阵分析与实验结果均表明,该超结构光纤光栅的透射谱呈现分形结构,在中心波长附近有六循环和自相似特性.所制备超结构光栅可作为C波段分形结构滤波器件在光通信和全光集成领域得到应用.     

基于多重分形去趋势波动分析法的交通流多重分形无标度区间自动识别方法

无标度区间是时间序列在统计意义上存在分形自相似性的尺度范围,是交通流多重分形特征研究中的重要组成部分.为解决交通流多重分形研究中多重分形去趋势波动分析法(multi-fractal detrended fluctuation analysis,MF-DFA)缺乏有效识别无标度区间方法的问题,本文在分析算法过程中交通流波动函数对数曲线突变点性质的基础上,结合传统无标度区间识别方法的构建思想,建立基于MF-DFA算法的无标度区间自动识别方法.以北京市二环快速路外环方向的部分道路为例开展实例研究,通过与传统无标度区间识别方法的结果对比,验证新方法的有效性.研究结果表明:本文方法能自动识别交通流多重分形无标度区间,且稳定性好;案例研究可知交通流短时间内波动较小、自相似性较强,随着研究时间段变长、交通流波动逐渐变大,自相似性逐渐消失,进一步解释了交通流无标度区间的有限性.     

Distribution of anomalous exponents of natural images

Recent studies of correlations of intensity in databases of natural images revealed a remarkable property. The two point correlations are described in terms of power law behavior, with an exponent which seems to be robust. In the present Letter we consider the statistical meaning of that result. We study many individual images of one of the databases considered. We find that the same law characterizing the correlations in the whole database governs also images randomly chosen from that database, with one essential difference. The exponent characterizing each image is specific and differs from the exponent characterizing the whole database. The distribution of single image exponents has been measured and found to exhibit a rather heavy tail. The database exponent cannot, thus, be considered as a statistical representative of a single image exponent. Possible reasons for the diversity in image exponents are discussed.     

基于信息分配和扩散理论的东北地区干旱脆弱性特征分析

基于信息分配和扩散理论, 结合标准化降水指数和东北三省(黑龙江、吉林、辽宁)旱灾灾损指数, 综合考虑了气象因子与社会因子, 分析了我国东北三省1971–2012年的干旱脆弱性特征, 并进一步计算了我国东北三省的干旱风险. 使用信息分配方法估计干旱强度概率分布, 采用二维正态信息扩散方法构造了干旱强度与旱灾灾损的脆弱性关系, 将干旱强度的概率分布与脆弱性折线相乘求和(离散分布)或积分(连续分布)即可得到多年平均风险. 研究表明, 针对灾损的小样本事件引入信息分配和扩散方法对小样本数据进行分析, 获取的干旱强度概率分布比简单直方图法所得更加平滑, 而以事件为因、灾损为果得到干旱强度-旱灾灾损的脆弱性关系, 物理意义明确, 所得脆弱性关系折线也比较符合实际情况, 并且不同样本长度所得结果相近, 对样本长度不敏感, 较好地克服了小样本分析的不稳定性. 关键词： 信息分配和扩散理论 标准化降水指数 脆弱性 风险     

基于幂律尾指数研究中国降水的时空演变特征

基于中国气象局国家气候中心740站点1960—2000a的日降水观测资料，对中国各地区日降水量分等级进行统计分析，揭示了各地区日降水存在的一个共同特征——幂律尾分布，且不同等级的降水量对应不同的幂律尾指数，在一定程度上反映了不同雨型具有不同的气候背景和物理机理.中国华北、华南等七个气候特征区，其幂律尾指数总体自东南向西北呈递增趋势，这与中国降水东多西少，南多北少的空间分布特征相符合.研究各气候特征区日降水的幂律尾指数随时间的演变特征发现：东北、华北和西北地区的幂律尾指数发生突变的年份对应着20世纪70年代末开始的中国北方干旱化进程，导致的可能原因是微量降水，尤其是0—7mm日降水的减少. 关键词： 幂律尾指数 突变 北方干旱化     

Unpredictability of the Wada property in the parameter plane

We show a type of unpredictability of the Wada property in the parameter plane for fixed initial conditions. This property indicates a larger unpredictability of sensitive dependence on parameters except for the riddled parameter sets. We describe some numerical experiments giving evidences of the parameter Wada property for different types of attractors including strange nonchaotic attractors. A scaling exponent is used to characterize sensitive dependence on parameters. We present a qualitative explanation on the occurrence of the Wada property in the parameter plane.     

Critical phenomena in a disc-percolation model and their application to relativistic heavy ion collisions

By studying the critical phenomena in continuum-percolation of discs, we find a new approach to locate the critical point, i.e.using the inflection point of P_∞ as an evaluation of the percolation threshold.The susceptibility, defined as the derivative of P_∞, possesses a finite-size scaling property, where the scaling exponent is the reciprocal of ν, the critical exponent of the correlation length.A possible application of this approach to the study of the critical phenomena in relativistic heavy ion collisions is discussed.The critical point for deconfinement can be extracted by the inflection point of P_(QGP)-the probability for the event with QGP formation.The finite-size scaling of its derivative can give the critical exponent ν, which is a rare case that can provide an experimental measure of a critical exponent in heavy ion collisions.     

Modeling network traffic using generalized Cauchy process

Processes with long-range dependence (LRD) have gained wide applications in many fields of science and technologies ranging from hydrology to network traffic. Two key properties of such processes are LRD that is characterized by the Hurst parameter H and self-similarity (SS) that is measured by the fractal dimension D. However, in the popular traffic model using fractional Gaussian noise (fGn), these two parameters are linearly related. This may be regarded as a limitation of fGn in traffic modeling from the point of view of either accurately fitting real traffic or appropriately explaining the particular multi-fractal phenomena of traffic. In this paper, we discuss recent results in traffic modeling from a view of the generalized Cauchy (GC) process. The GC process is indexed by two parameters D and H. The parameter D in the GC model is independent of H. Hence, it provides a more flexible way to describe the multi-fractal phenomena of traffic in addition to accurately modeling traffic for both short-term lags and long-term ones.     

风电功率时间序列混沌特性分析及预测模型研究

为揭示风电功率序列内在的动态特性, 利用非线性方法对风电时间序列混沌特性进行识别, 为对风电功率进行预测提供了基础.首先对某风电场的风电功率时间序列的日相关性进行了分析;然后在相空间重构的基础上计算了风电序列的最大Lyapunov指数, 验证了风电时间序列的混沌特性;由于采用Volterra滤波器多步预测法对风电功率进行超短期预测误差较大, 利用局域多步预测法以及最大Lyapunov指数法的预测结果并结合加权马尔科夫链和有序算子对Volterra滤波器的预测结果进行校正.最后以某实际风电场的风电功率预测为算例, 仿真结果表明校正预测模型有效的提高了预测精度, 其为利用Volterra滤波器多步法进行风电预测提供了有益的参考.     

Chaotic quivering of micron-scaled on-chip resonators excited by centrifugal optical pressure

Opto-mechanical chaotic oscillation of an on-chip resonator is excited by the radiation-pressure nonlinearity. Continuous optical input, with no external feedback or modulation, excites chaotic vibrations in very different geometries of the cavity (both tori and spheres) and shows that opto-mechanical chaotic oscillations are an intrinsic property of optical microcavities. Measured phenomena include period doubling, a spectral continuum, aperiodic oscillations, and complex trajectories. The rate of exponential divergence from a perturbed initial condition (Lyapunov exponent) is calculated. Continuous improvements in cavities mean that such chaotic oscillations can be expected in the future with many other platforms, geometries, and frequency spans.