Parameter estimation using balanced synchronization

Synchronization between experimental observations and a dynamical model with undetermined parameters can assist in completing the specification of the model parameters. The quality of the synchronization, a cost function to be minimized, typically depends on the difference between the data time series and the model time series. If the coupling between the data and the model is too strong, this cost function is small for any data and any model, and the variation of the cost function with respect to the parameters of interest is too small to permit selection of a value of the parameters. If the coupling is too small, synchronization is lost. We introduce two methods for balancing the competing desires of a small cost function and the numerical ability to determine parameters accurately. One method of ‘balanced’ synchronization adds a requirement that the conditional Lyapunov exponent of the model system, conditioned on being driven by the data, remain negative but small. The other method allows the coupling to vary in time according to the error in synchronization. This second method succeeds because the data and the model exhibit generalized synchronization in the region where the parameters of the model are well determined.     

Parameter identification and synchronization of spatiotemporal chaos in an uncertain Gray-Scott system

The zero-asymptotic property of sliding variables in discrete systems is extended to a continuous one and applied to partial differential equations which describe spatiotemporal chaos. A method of chaos synchronization and parameter identification is proposed. The synchronization controllers and the parameter recognizers are designed. The uncertain Gray-Scott system is taken as an example to verify the effectiveness of the method. Simulation results show that the identification variables in the parameter recognizers may take the place of the unknown parameters in both target and response systems. Global synchronization of the two spatiotemporal chaotic systems with uncertain parameters may be realized quickly after controllers are added. Supported by the Natural Science Foundation of Liaoning Province, China (Grant No. 20052151) and the Innovative Team Program of Liaoning Educational Committee     

Detecting anomalous phase synchronization from time series

Modeling approaches are presented for detecting an anomalous route to phase synchronization from time series of two interacting nonlinear oscillators. The anomalous transition is characterized by an enlargement of the mean frequency difference between the oscillators with an initial increase in the coupling strength. Although such a structure is common in a large class of coupled nonisochronous oscillators, prediction of the anomalous transition is nontrivial for experimental systems, whose dynamical properties are unknown. Two approaches are examined; one is a phase equational modeling of coupled limit cycle oscillators and the other is a nonlinear predictive modeling of coupled chaotic oscillators. Application to prototypical models such as two interacting predator-prey systems in both limit cycle and chaotic regimes demonstrates the capability of detecting the anomalous structure from only a few sets of time series. Experimental data from two coupled Chua circuits shows its applicability to real experimental system.     

Detecting synchronizations in an asymmetric vocal fold model from time series data

A nonlinear modeling approach is presented for the reconstruction of the synchronization structure in an asymmetric two-mass model from time series data. The asymmetric two-mass model describes a variety of normal and pathological human voices associated with synchronous and desynchronous oscillations of the two asymmetric vocal folds. Our technique recovers the synchronization diagram, which yields the regimes of synchronization as well as desynchronization, which are dependent upon the asymmetry parameter and the subglottal pressure. This allows the prediction of the regime of pathological phonation associated with desynchronization of the vocal folds from a few sets of recorded time series. It is shown that the modeling is quite effective when the time series data are chaotic and if they are taken from a regime of desynchronization. We discuss the applicability of the present approach as a diagnostic tool for voice pathologies.     

基于差分进化算法的混沌时间序列预测模型参数组合优化

为了提高混沌时间序列预测模型的预测精度,提出一种基于差分进化（DE）算法的相空间重构和最小二乘支持向量机（LSSVM）模型参数组合优化方法．该方法将相空间重构参数和LSSVM预测模型参数进行组合作为差分进化算法的个体,以混沌时间序列预测精度作为个体的适应度函数,通过循环迭代获得最优参数组合．几个混沌时间序列的仿真实验结果表明,与传统的优化方法相比,参数组合优化方法具有更高的预测精度．     

Parameter estimation for the piecewice-polynomial mean value trend of a stochastic time series

We consider the problem of mean value trend estimation for a stochastic time series in a mixture with noise. The trend is simulated as a polynomial function of time with parameters changing discontinuously at a random instant. The proposed solution of this problem is based on the optimal nonlinear filtering theory for pulsed Markovian processes. An algorithm for approximate estimation of piesewise-linear trend parameters is devised as an example. The results of numerical simulation of a synthesized algorithm are presented. Lobachevsky State University, Nizhny Novgorod, Russia. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 40, No. 11, pp. 1405–1415, November, 1997.     

地块支持下MODIS-NDVI时间序列冬小麦种植面积测量研究

在大尺度冬小麦种植面积测量中,MODIS(moderate resolution imaging spectrometer)数据对绝大部分地区可实现全覆盖数据保障,具有很好的时间序列特征,在探测植物季相节律进行作物估产与动态监测上得到很好的应用,但因受到空间分辨率的限制,其测量结果的可靠性受到较大质疑.地块数据具有明确...     

全局耦合网络的参量辨识与时空混沌同步

研究了参量未知的离散型时空混沌系统构成全局耦合网络的参量辨识与同步问题.首先将Milosavljevic所设计的控制律加以推广.利用推广后的控制律进行了网络节点时空混沌系统中未知参量的有效辨识,并完成了该网络的完全同步.进一步以物理中具有时空混沌行为的一维对流方程的离散形式作为实例进行了仿真分析. 关键词： 同步 参量辨识 全局耦合网络 时空混沌     

Parameter estimation based synchronization for an epidemic model with application to tuberculosis in Cameroon

We propose a method based on synchronization to identify the parameters and to estimate the underlying variables for an epidemic model from real data. We suggest an adaptive synchronization method based on observer approach with an effective guidance parameter to update rule design only from real data. In order, to validate the identifiability and estimation results, numerical simulations of a tuberculosis (TB) model using real data of the region of Center in Cameroon are performed to estimate the parameters and variables. This study shows that some tools of synchronization of nonlinear systems can help to deal with the parameter and state estimation problem in the field of epidemiology. We exploit the close link between mathematical modelling, structural identifiability analysis, synchronization, and parameter estimation to obtain biological insights into the system modelled.     

Theoretical and experimental studies of parameter estimation based on chaos feedback synchronization

In this paper, we perform theoretical and experimental studies of parameter estimation based on chaos feedback synchronization. The Chua chaotic system is applied as the original system, and its time series of a single variable is applied as a feedback variable to drive a simulative system. The simplex method is employed to minimize the synchronization error in the simulative system to iteratively approach the original system parameters. Furthermore, the effects of feedback function, feedback weight, and noise are investigated. The parameter estimation method based on feedback synchronization shows its robustness to noise perturbation. Finally, the circuit experiment of parameter estimation is implemented in order to examine its practical applicability. The original Chua circuit parameters can be well approached from its recorded time series of a single variable. The results show the parameter estimation method based on feedback synchronization may be capable of estimating real system parameters from a chaotic time series.     

Multiparameter estimation using only a chaotic time series and its applications

An important extension to the techniques of synchronization-based parameter estimation is presented. Based on adaptive chaos synchronization, several methods are proposed to dynamically estimate multiple parameters using only a scalar chaotic time series. In comparison with previous schemes, the presented methods decrease the cost of parameter estimation and are more applicable in practice. Numerical examples are used to demonstrate the effectiveness and robustness of the presented methods. As an example application, an implementation of multichannel digital communication is proposed, where multiparameter modulation is used to simultaneously transmit more than one digital message. From a theoretical perspective, such an encoding increases the difficulty to directly read out the message from the transmitted signal and decreases the implementation cost.     

一种基于有源backstepping设计的混沌和超混沌系统的广义同步方法研究

本文提出了一种新颖的有源backstepping控制设计方法用于实现两个相同R?ssler超混沌系统的同步,并进一步将该方法推广到实现Chua混沌系统和R?ssler超混沌系统的广义同步。由于该设计方法在控制器设计的每一步中都能将Lyapunov函数的选择和有源控制器的设计紧密地结合起来考虑,从而能根据工程实际灵活地构造出合适的控制器以满足系统控制要求,同时也为控制器的设计提供了一种系统的设计方法。这正是这种设计方法的最大优点。数值结果表明了本文所提出设计方法的可行性和有效性。     

Parameter identification and synchronization of an uncertain Chen chaotic system via adaptive control

A systematic design process of adaptive synchronization and parameter identification of an uncertain Chen chaotic system is provided.With this new and effective method,parameter identification and synchronization of the Chen system,with all the system parameters unknown,can be achieved simultaneously.Theoretical proof and numerical simulation demonstrate the effectiveness and feasibility of the proposed method.     

非线性耦合完全网络的时空混沌同步

利用N个Fitzhugh-Nagumo模型作为网络节点,通过非线性耦合构成完全网络,研究了这种网络的时空混沌同步问题.首先给出了复杂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.进一步基于Lyapunov稳定性定理,理论分析了实现网络同步的条件以及控制增益的取值范围.最后,通过仿真模拟检验了以Fitzhugh-Nagumo模型作为网络节点所构成的完全网络的时空混沌同步效果.仿真结果表明,这种完全网络不但同步快速有效,而且网络规模的大小对网络同步稳定性的影响不敏感. 关键词： 同步 复杂网络 时空混沌 非线性耦合     

Impact of modulated multiple optical feedback time delays on laser diode chaos synchronization

By studying laser diodes subject to multiple time-delayed optical feedback, we demonstrate that the signatures of time delays in the autocorrelation function of the laser output can be erased in systems incorporating modulated feedback time delays. This property enhances the suitability of such laser systems highly suitable for secure chaos-based communication systems. Chaos synchronization properties of a laser-based modulated multiple time-delayed system are also reported for the first time.     

双路激光混沌复用系统的混沌同步及安全性能研究

针对一种新型的双路激光混沌复用系统, 建立相应的速率方程模型, 详细分析了两个主激光器的单个参数失配、多个参数同时失配、反馈强度差异以及频率失谐对混沌同步性能的影响, 并对此复用系统的安全性能和频谱性能进行了研究. 研究结果表明: 采用参数失配方案, 通过合理选择两个主激光器的参数, 可以保证两个主激光器之间的同步性能较差而两对主从激光器间实现高品质的混沌同步, 因此满足双路激光混沌复用的条件; 两个主激光器之间的参数失配对它们之间的同步性能影响较大, 然而对配对主从激光器间同步性能的影响并不明显, 进一步说明参数失配方案的有效性和可行性. 另外, 通过自相关函数和频谱分别分析混沌复用信号的时域和频域特征, 发现双路激光混沌复用系统可提供更高的安全性.     

一个简单延迟非线性系统的动力学行为及混沌同步

分析一个简单二阶延迟系统的Hopf分支和混沌特性, 包括分支点、分支方向和分支周期解的稳定性, 解析求出退延迟情况下, 这个系统的相轨线方程; 通过数值计算并绘制分岔图, 揭示系统存在由倍周期通向混沌的道路; 利用单路线性组合信号, 反馈控制实现系统的部分完全同步; 利用主动-被动与线性反馈的联合, 实现系统的完全同步; 设计和搭建系统的电子实验线路, 并从实验中观测到与理论分析或数值计算相一致的结果. 关键词： 延迟非线性系统 电路实验 Hopf分支 混沌     

The dynamics of exchange rate time series and the chaos game

This work presents a novel method of reconstructing some relevant characteristics of exchange rate time series by the superposition of two components: a mostly deterministic one, the chaos game as expressed by the Yuan/USD exchange rate and a purely stochastic one, Gaussian white noise. We analyzed 20 economic systems with the average Index of Economic Freedom above 50. The considered characteristics (the Lempel-Ziv complexity index, the slimness of the distribution and the Iterated Function Systems clumpiness test) are well reproduced by the reconstruction process. Additional confirmation is obtained by an analysis of the exchange rate of the Romanian national currency as an example of an application of the method to a transition economy, and by an analysis of the time series of the Euro-zone as an example of an application to a multinational system using a shorter time series.     

不确定Chen系统的参数辨识与自适应同步

研究了不确定Chen系统的自适应同步和参数辨识，设计了自适应控制器和参数更新规则，理论证明了该控制器可使得两个Chen系统——驱动系统和未知参数的响应系统渐进地达到同步，并且可以辨识出响应系统的未知参数.数值模拟结果证明了该控制器的有效性. 关键词： 不确定Chen系统 自适应同步 参数辨识 控制器