Analyses of Optimal Embedding Dimension and Delay for Local Linear Prediction Model

In the reconstructed phase space, a novel local linear prediction model is proposed to predict chaotic time series. The parameters of the proposed model take the values that are different from those of the phase space reconstruction. We propose a criterion based on prediction error to determine the optimal parameters of the proposed model. The simulation results show that the proposed model can effectively make one-step and multistep prediction for chaotic time series, and the one-step and multi-step prediction accuracy of the proposed model is superior to that of the traditional local linear prediction.     

Synchronization in coupled nonidentical incommensurate fractional-order systems

Synchronization of fractional-order nonlinear systems has received considerable attention for many research activities in recent years. In this Letter, we consider the synchronization between two nonidentical fractional-order systems. Based on the open-plus-closed-loop control method, a general coupling applied to the response system is proposed for synchronizing two nonidentical incommensurate fractional-order systems. We also derive a local stability criterion for such synchronization behavior by utilizing the stability theory of linear incommensurate fractional-order differential equations. Feasibility of the proposed coupling scheme is illustrated through numerical simulations of a limit cycle system, a chaotic system and a hyperchaotic system.     

Is the Hamiltonian geometrical criterion for chaos always reliable?

It is found that the application of a newly developed geometrical criterion, in which negative eigenvalues of the associated matrix determined by the dynamical curvature of a conformal metric for a Hamiltonian system are used to identify the onset of local instability or chaos, is somewhat problematic in some circumstances. In fact, this criterion is neither necessary nor sufficient for the prediction of instability of orbits on a same energy hypersurface because it is not in good agreement with information on unstable or chaotic behavior given by the maximal Lyapunov exponent in general.     

Secure and Efficient Pseudorandom Bit Generator for Chaotic Stream Ciphers

Based on the entropy criterion and n-dimensional uniform distribution of nonlinear digital filter （NDF）, we present an efficient NDF-based pseudorandom bit generator （NDF-PRBG） for chaotic stream ciphers. The cryptographic properties of the proposed NDF-PRBG are analysed, and some experiments are made. The results show that it has desirable cryptographic properties, and can be used to construct secure stream ciphers with high speed.     

Qualitative analysis of the Rössler equations: Bifurcations of limit cycles and chaotic attractors

In this paper we study different aspects of the paradigmatic Rössler model. We perform a detailed study of the local and global bifurcations of codimension one and two of limit cycles. This provides us a global idea of the three-parametric evolution of the system. We also study the regions of parameters where we may expect a chaotic behavior by the use of different Chaos Indicators. The combination of the different techniques gives an idea of the different routes to chaos and the different kinds of chaotic attractors we may found in this system.     

Propensity criterion for networking in an array of coupled chaotic systems

We examine the mutual synchronization of a one-dimensional chain of chaotic identical objects in the presence of a stimulus applied to the first site. We first describe the characteristics of the local elements, and then the process whereby a global nontrivial behavior emerges. A propensity criterion for networking is introduced, consisting in the coexistence within the attractor of a localized chaotic region, which displays high sensitivity to external stimuli, and an island of stability, which provides a reliable coupling signal to the neighbors in the chain. Based on this criterion, we compare homoclinic chaos, recently explored in lasers and conjectured to be typical of a single neuron, with Lorenz chaos.     

Recurrence network analysis of experimental signals from bubbly oil-in-water flows

Based on the signals from oil–water two-phase flow experiment, we construct and analyze recurrence networks to characterize the dynamic behavior of different flow patterns. We first take a chaotic time series as an example to demonstrate that the local property of recurrence network allows characterizing chaotic dynamics. Then we construct recurrence networks for different oil-in-water flow patterns and investigate the local property of each constructed network, respectively. The results indicate that the local topological statistic of recurrence network is very sensitive to the transitions of flow patterns and allows uncovering the dynamic flow behavior associated with chaotic unstable periodic orbits.     

Universality of level spacing distributions in classical chaos

We suggest that random matrix theory applied to a matrix of lengths of classical trajectories can be used in classical billiards to distinguish chaotic from non-chaotic behavior. We consider in 2D the integrable circular and rectangular billiard, the chaotic cardioid, Sinai and stadium billiard as well as mixed billiards from the Limaçon/Robnik family. From the spectrum of the length matrix we compute the level spacing distribution, the spectral auto-correlation and spectral rigidity. We observe non-generic (Dirac comb) behavior in the integrable case and Wignerian behavior in the chaotic case. For the Robnik billiard close to the circle the distribution approaches a Poissonian distribution. The length matrix elements of chaotic billiards display approximate GOE behavior. Our findings provide evidence for universality of level fluctuations—known from quantum chaos—to hold also in classical physics.     

A new local linear prediction model for chaotic time series

A new local linear prediction model is proposed to predict chaotic time series in this Letter. We propose that the parameters—the embedding dimension and the time delay of the local linear prediction model—can take values which are different to those of the state space reconstruction in the procedure of finding the nearest neighbor points. We propose a criterion based on prediction power to determine the optimal parameters of the new local linear prediction model. Simulation results show that the new local linear prediction model can effectively predict chaotic time series and the prediction performance of the new local linear prediction model is superior to that of the local linear prediction.     

Chaos in a fractional-order micro-electro-mechanical resonator and its suppression

The present paper investigates the existence of chaos in a non-autonomous fractional-order micro-electromechanical resonator system(FOMEMRS).Using the maximal Lyapunov exponent criterion,we show that the FOMEMRS exhibits chaos.Strange attractors of the system are plotted to validate its chaotic behavior.Afterward,a novel fractional finite-time controller is introduced to suppress the chaos of the FOMEMRS with model uncertainties and external disturbances in a given finite time.Using the latest version of the fractional Lyapunov theory,the finite time stability and robustness of the proposed scheme are proved.Finally,we present some computer simulations to illustrate the usefulness and applicability of the proposed method.     

Chaotic Dynamics of a Josephson Junction with a Ratchet Potential and Current-Modulating Damping

The chaotic dynamics of a Josephson junction with a ratchet potential and current-modulating damping are studied. Under the first-order approximation, we construct the general solution of the first-order equation whose boundedness condition contains the famous Melnikov chaotic criterion. Based on the general solution, the incomputability and unpredictability of the system’s chaotic behavior are discussed. For the case beyond perturbation conditions, the evolution of stroboscopic Poincaré sections shows that the system undergoes a quasi-periodic transition to chaos with an increasing intensity of the rf-current. Through a suitable feedback controlling strategy, the chaos can be effectively suppressed and the intensity of the controller can vary in a large range. It is also found that the current between the two separated superconductors increases monotonously in some specific parameter spaces.     

玻色-爱因斯坦凝聚系统中原子的空间混沌分布

研究了非对称周期势阱中玻色-爱因斯坦凝聚原子的空间混沌分布结构. 在凝聚体相位为常数的情况下, 凝聚体内部不存在原子流,凝聚原子的空间分布结构可以用一个无阻尼双驱动Duffing方程描述. 理论分析给出了原子间呈排斥作用系统的Mel'nikov混沌判据.数值模拟结果显示,化学势的增大能够对原子混沌分布产生明显的抑制作用,甚至使混沌完全消失. 对于原子间呈吸引作用的系统,在一定参数条件下,调节光格势强度比可以使凝聚原子由周期状态进入到空间混沌分布状态,随着化学势的增大这种空间混沌分布被完全抑制. 关键词： 玻色-爱因斯坦凝聚 Mel'nikov函数 混沌     

双参数激光振荡输出系统中混沌的控制规律

研究了双参数激光振荡输出系统中混沌行为的控制问题，给出了控制混沌的不同参数变化方程，并进行了比较.数值计算结果表明：随着控制参数的改变，激光振荡输出的混沌态可控制到1周期、2周期、…2ⁿ周期.控制混沌的参数变化方程遵循特定的规律.最后，对相关问题进行了分析和讨论. 关键词：     

The improved local linear prediction of chaotic time series

Based on the Bayesian information criterion, this paper proposes the improved local linear prediction method to predict chaotic time series. This method uses spatial correlation and temporal correlation simultaneously. Simulation results show that the improved local linear prediction method can effectively make multi-step and one-step prediction of chaotic time series and the multi-step prediction performance and one-step prediction accuracy of the improved local linear prediction method are superior to those of the traditional local linear prediction method.     

混沌噪声背景下微弱脉冲信号的检测及恢复

构建了一种在混沌噪声背景下检测并恢复微弱脉冲信号的模型.首先,基于混沌信号的短期可预测性及其对微小扰动的敏感性,对观测信号进行相空间重构、建立局域线性自回归模型进行单步预测,得到预测误差,并利用假设检验方法从预测误差中检测观测信号中是否含有微弱脉冲信号.然后,对微弱脉冲信号建立单点跳跃模型,并融合局域线性自回归模型,构成双局域线性(DLL)模型,以极小化DLL模型的均方预测误差为目标进行优化,采用向后拟合算法估计模型的参数,并最终恢复出混沌噪声背景下的微弱脉冲信号.仿真实验结果表明本文所建的模型能够有效地检测并恢复出混沌噪声背景中的微弱脉冲信号.     

Floquet states and geometrical phase of a multi-level system in cyclic evolution

We study the electronic states of a mesoscopic system whose Hamiltonian has a complicated static multi-level energy structure and undergoes periodic evolution in time. By using the Floquet theory, we derive the quasienergies, the Floquet states, and the geometrical phase. It is shown numerically that the geometrical phase is strongly dependent on the evolution circuits in the parameter space and on the evolution frequency of the varying Hamiltonian. In some cases the nonadiabatic geometric phases can exhibit chaotic behavior. We also show a trend of phase compensation in pairs of states which could restore the phase coherence if the pairing occurs.     

Nonlinear Local Lyapunov Exponent and Quantification of Local Predictability

Nonlinear local Lyapunov exponent （NLLE） is applied to quantitatively determine the local predictability limit of chaotic systems. As an example, we find that the local predictability limit of Henon attractor varies considerably with time, and some underlying phase-spatial structure does not appear. The local predictability limit of initially adjacent points in phase space may be completely different. This will cause difficulties in making the long-time analogue forecast.     

Dynamical effects of a one-dimensional multibarrier potential of finite range

We discuss the properties of a large number N of one-dimensional (bounded) locally periodic potential barriers in a finite interval. We show that the transmission coefficient, the scattering cross section σ, and the resonances of σ depend sensitively upon the ratio of the total spacing to the total barrier width. We also show that a time dependent wave packet passing through the system of potential barriers rapidly spreads and deforms, a criterion suggested by Zaslavsky for chaotic behaviour. Computing the spectrum by imposing (large) periodic boundary conditions we find a Wigner type distribution. We investigate also the S-matrix poles; many resonances occur for certain values of the relative spacing between the barriers in the potential. Received 1st August 2001 and Received in final form 18 November 2001     

Chaotic motion of Van der Pol–Mathieu–Duffing system under bounded noise parametric excitation

The chaotic behavior of Van der Pol–Mathieu–Duffing oscillator under bounded noise is investigated. By using random Melnikov technique, a mean square criterion is used to detect the necessary conditions for chaotic motion of this stochastic system. The results show that the threshold of bounded noise amplitude for the onset of chaos in this system increases as the intensity of the noise in frequency increases, which is further verified by the maximal Lyapunov exponents of the system. The effect of bounded noise on Poincaré map is also investigated, in addition the numerical simulation of the maximal Lyapunov exponents.