Detecting nonlinearity of action surface EMG signal

The action surface EMG (ASEMG) signal contains the electrical properties of limb muscle contraction that undergo many complex transitions in limb different movement states; however, because of the small data nature of this kind signal, it is not clear whether its essence is stochastic or deterministic nonlinear (even chaotic). In this Letter, we show for the first time that ASEMG has deterministic nonlinear character by using the surrogate data method. Furthermore, we study the nonlinear dynamic features of ASEMG by computing its correlation dimension and applying correlation dimension as test statistics. These results indicate that ASEMG is a high-dimension nonlinear signal (even chaotic). In addition, this Letter improves the surrogate data method based on Fourier transform (FT) algorithm to avoid limitations of the previous FT algorithm.     

非线性动力系统分岔图中的暗线

基于非线性动力系统混沌运动的回归特性，构造了一种对分岔图中穿过混沌区的暗线进行研究的数值回归算法。运用该算法求得抛物线映射的暗线，并与通过暗线方程精确求得的暗线进行比较，验证了算法的有效性。对Brussel振子系统和分段线性单级齿轮动力系统的暗线进行了研究。通过对非线性动力系统分岔图中暗线的研究，由其切点可以得到嵌在混沌区中的周期窗口，由其交点可以得到混沌吸引子的激变点。研究结果表明该算法有助于分析系统的动力学行为和控制混沌运动。     

A New Hyperchaotic 4D-FDHNN System with Four Positive Lyapunov Exponents and Its Application in Image Encryption

In this paper, a hyperchaotic four-dimensional fractional discrete Hopfield neural network system (4D-FDHNN) with four positive Lyapunov exponents is proposed. Firstly, the chaotic dynamics’ characteristics of the system are verified by analyzing and comparing the iterative trajectory diagram, phase diagram, attractor diagram, 0-1 test, sample entropy, and Lyapunov exponent. Furthermore, a novel image encryption scheme is designed to use the chaotic system as a pseudo-random number generator. In the scenario, the confusion phase using the fractal idea proposes a fractal-like model scrambling method, effectively enhancing the complexity and security of the confusion. For the advanced diffusion phase, we proposed a kind of Hilbert dynamic random diffusion method, synchronously changing the size and location of the pixel values, which improves the efficiency of the encryption algorithm. Finally, simulation results and security analysis experiments show that the proposed encryption algorithm has good efficiency and high security, and can resist common types of attacks.     

离散混沌系统的最小能量控制

对于离散混沌系统的最小能量控制问题，提出了一种框架性方法，该方法具有通用性.首先，设计一个二次目标函数，同时把混沌系统分解为线性部分和非线性部分两项和.然后，提出了求解非线性最优控制问题的两级算法：第一级对混沌系统中的非线性部分进行预估，以使原系统变为带有常数项的线性系统；第二级用动态规划求解一个非典型线性二次最优控制问题，并把解返回第一级，第一级根据第二级的解对非线性部分重新预估.这样通过两级间不断的信息交换，最终得到混沌系统的最优控制律.该方法不仅实现了对混沌系统的控制，而且在整个控制过程中消耗的控制能量最小. 关键词： 混沌系统 两级优化 最优控制     

分数阶混沌系统的Adomian分解法求解及其复杂性分析

根据分数阶微分定义,采用Adomian分解算法,研究了分数阶简化Lorenz系统的数值解.研究发现,该算法与预估-校正算法相比,求解结果更准确,所耗计算资源和内存资源更少,求解整数阶系统时较Runge-Kutta算法更准确;利用Adomian算法得到的分数阶简化Lorenz系统出现混沌的最小阶数为1.35,比利用预估-校正算法得到的最小阶2.79更小.采用相图、分岔图分析了该系统的动力学特性,基于谱熵算法(SE)和C0算法分析了该系统的复杂度.结果表明,复杂度结果和分岔图一致,说明系统的复杂度同样能反映出系统动力学特性;复杂度随阶数q的增加呈总体减小的趋势,而混沌态时系统参数c变化对系统复杂度影响不大.为分数阶混沌系统应用于信息加密、保密通信领域提供了理论与实验依据.     

基于模糊模型的混沌时间序列预测

对于复杂、病态、非线性动态系统，基于模糊集合的模糊模型，利用模糊推理规则描述动态系统的特性，是一种有效方法.讨论了利用模糊建模方法实现非线性系统的建模和预测.首先，利用在线模糊竞争学习方法划分输入变量的模糊输入空间，然后利用卡尔曼滤波算法估计模糊模型的参数.采用该方法对Mackey Glass混沌时间序列进行预测试验，结果表明利用本方法可以在线或者离线能对Mackey Glass混沌时间序列进行准确预测，证明了本方法的有效性. 关键词： 模糊竞争学习 混沌时间序列 卡尔曼滤波     

Probing quantum dissipative chaos using purity

In this Letter, the purity of quantum states is applied to probe chaotic dissipative dynamics. To achieve this goal, a comparative analysis of regular and chaotic regimes of nonlinear dissipative oscillator (NDO) are performed on the base of excitation number and the purity of oscillatory states. While the chaotic regime is identified in our semiclassical approach by means of strange attractors in Poincaré section and with the Lyapunov exponent, the state in the quantum regime is treated via the Wigner function. Specifically, interesting quantum purity effects that accompany the chaotic dynamics are elucidated in this Letter for NDO system driven by either: (i) a time-modulated field, or (ii) a sequence of pulses with Gaussian time-dependent envelopes.     

On Physically Unacceptable Numerical Solutions Yielding Strong Chaotic Signals

Physically unacceptable chaotic numerical solutions of nonlinear circuits and systems are discussed in this paper. First, as an introduction, a simple example of a wrong choice of a numerical solver to deal with a second-order linear ordinary differential equation is presented. Then, the main result follows with the analysis of an ill-designed numerical approach to solve and analyze a particular nonlinear memristive circuit. The obtained trajectory of the numerical solution is unphysical (not acceptable), as it violates the presence of an invariant plane in the continuous systems. Such a poor outcome is then turned around, as we look at the unphysical numerical solution as a source of strong chaotic sequences. The 0–1 test for chaos and bifurcation diagrams are applied to prove that the unacceptable (from the continuous system point of view) numerical solutions are, in fact, useful chaotic sequences with possible applications in cryptography and the secure transmission of data.     

基于复合非线性数字滤波器的Hash函数构造

在对多个满足Kelber条件的滤波器组成的复合系统进行初步分析的基础上，提出了一个基于复合非线性数字滤波器的带密钥的Hash算法.算法首先构建能产生高维混沌序列的复合滤波器系统，然后在明文作用的复合序列控制下随机选择滤波器子系统，并以复合系统的初态作为密钥，以粗粒化的量化迭代轨迹作为明文的Hash值.讨论了复合系统实现Hash函数的不可逆性、防伪造性、初值敏感性等特点.研究结果表明：基于复合非线性数字滤波器的Hash算法简单快速，比基于单一混沌映射的Hash算法有着更高的安全性，同时滤波器结构中没有复杂的浮点运算，比一般复合混沌系统更易于软硬件实现. 关键词： Hash 函数 混沌 非线性自回归数字滤波器     

基于指数加权-核在线序列极限学习机的混沌系统动态重构研究

利用指数加权在线核序列极限学习机(exponential weighted online sequential extreme learning machine with kernel, EW-KOSELM)辨识算法,开展了针对混沌动力学系统的动态重构研究. EW-KOSELM算法将核递归最小二乘(kernel recursive least squares, KRLS)算法直接延伸至在线ELM (extreme learning machine)框架中,通过引入遗忘因子削弱了旧数据的影响,并基于"固定预算(fixed-budget, FB)"内存技术,应对在线核学习算法所固有的规模不断增长的计算困难.将所提辨识算法应用于Duffing-Ueda振子的混沌动力学系统数值仿真实例中,对基于FB-EW-KOSELM的辨识模型与原系统的动态性能进行了定性与定量的分析校验,定性校验准则是基于对比辨识模型与原系统吸引子(轨迹嵌入)、庞加莱映射、分岔图、极限环完成的,定量校验准则包括对比辨识模型与原系统的李雅普诺夫指数与关联维.进一步将其分别应用于来自测量蔡氏电路产生双涡卷吸引子与螺旋吸引子的实测数据实验及某一实际混沌电路所产生的时间序列中,对于具有低信噪比的实测电压或电流数据还需进行了小波降噪预处理.通过分析辨识模型重构吸引子,实验结果表明,FB-EW-KOSELM算法具有良好的动态重构性能,能精确地再生出展示混沌动态行为的过程非线性模型,且具有与原混沌系统非常接近的动态不变性指标.     

混沌伪随机序列的谱熵复杂性分析

为了准确分析混沌伪随机序列的结构复杂性,采用谱熵算法对Logistic映射、Gaussian映射和TD-ERCS系统产生的混沌伪随机序列复杂度进行了分析.谱熵算法具有参数少、对序列长度N(惟一参数)和伪随机进制数K鲁棒性好的特点.采用窗口滑动法分析了混沌伪随机序列的复杂度演变特性,计算了离散混沌系统不同初值和不同系统参数条件下的复杂度.研究表明,谱熵算法能有效地分析混沌伪随机序列的结构复杂度;在这三个混沌系统中,TD-ERCS系统为广域高复杂度混沌系统,复杂度性能最好;不同窗口和不同初值条件下的混沌系统复杂度在较小范围内波动.为混沌序列在信息安全中的应用提供了理论和实验依据.     

一种新型广义RBF神经网络在混沌时间序列预测中的研究

提出了一种新颖的广义径向基函数神经网络模型,其径向基函数(RBF)的形式由生成函数确定.然后,给出了易实现的梯度学习算法,同时为了进一步提高网络的收敛速度和网络性能,又给出了基于卡尔曼滤波的动态学习算法.为了验证网络的学习性能，采用基于卡尔曼滤波算法的新型广义RBF网络预测模型对Mackey-Glass混沌时间序列和Henon映射进行了仿真.结果表明,所提出的新型广义RBF神经网络模型能快速、精确地预测混沌时间序列,是研究复杂非线性动力系统辨识和控制的一种有效方法. 关键词： 广义径向基函数神经网络 卡尔曼滤波 梯度下降学习算法 混沌时间序列 预测     

Analysis of chaotic non-isothermal solutions of thermomechanical shape memory oscillators

Shape memory materials exhibit strong thermomechanical coupling, so that temperature variations occur during mechanical loading and unloading. In previous works the nonlinear dynamics of pseudoelastic oscillators subject to an harmonic force has been studied and the possibility of non-regular chaotic responses has been thoroughly documented. Instead of the standard Lyapunov exponent treatment, the statistical 0–1 test based on the asymptotic properties of a Brownian motion chain was successively applied to reveal the chaotic nature of trajectories in the special case in which temperature variations were neglected. In this work, the 0–1 test is applied to fully non-isothermal trajectories. To improve its reliability the test has been applied to the time-histories of maxima and minima of each trajectory, in each component. The obtained results have been validated and confirmed by the corresponding Fourier spectra. Non-regular solutions with different levels of chaoticity have been analyzed and their qualitative difference is reflected by the different values to which the control parameter K asymptotically converge.     

Sequential reconstruction of driving-forces from nonlinear nonstationary dynamics

This paper describes a functional analysis-based method for the estimation of driving-forces from nonlinear dynamic systems. The driving-forces account for the perturbation inputs induced by the external environment or the secular variations in the internal variables of the system. The proposed algorithm is applicable to the problems for which there is too little or no prior knowledge to build a rigorous mathematical model of the unknown dynamics. We derive the estimator conditioned on the differentiability of the unknown system’s mapping, and smoothness of the driving-force. The proposed algorithm is an adaptive sequential realization of the blind prediction error method, where the basic idea is to predict the observables, and retrieve the driving-force from the prediction error. Our realization of this idea is embodied by predicting the observables one-step into the future using a bank of echo state networks (ESN) in an online fashion, and then extracting the raw estimates from the prediction error and smoothing these estimates in two adaptive filtering stages. The adaptive nature of the algorithm enables to retrieve both slowly and rapidly varying driving-forces accurately, which are illustrated by simulations. Logistic and Moran-Ricker maps are studied in controlled experiments, exemplifying chaotic state and stochastic measurement models. The algorithm is also applied to the estimation of a driving-force from another nonlinear dynamic system that is stochastic in both state and measurement equations. The results are judged by the posterior Cramer-Rao lower bounds. The method is finally put into test on a real-world application; extracting sun’s magnetic flux from the sunspot time series.     

Generation and circuit implementation of multi-block multidirectional grid multi-scroll chaotic attractors

Due to the dynamic characteristics of the Chua's system, multi-scroll chaotic attractors are still confined in a single block and fail to break the limit. This paper proposes an approach for generating novel multi-block multidirectional grid multi-scroll chaotic attractors that can break the limit via novel nonlinear modulating functions. According to this method, the recursion rules used to generate multi-block multidirectional grid multi-scroll attractors are mathematically obtained. The new system is autonomous; the effectiveness of this method has been verified by theoretical analysis, numerical simulation, and circuit implementation.     

将混沌序列变换成均匀伪随机序列的普适算法

提出了一种将混沌序列变换成均匀伪随机序列的普适算法.这种算法基于计算机浮点数表示的bit位操作,不针对任何具体对象,可将任意连续或分段连续分布的实型随机变量转换成均匀分布的随机变量.理论分析表明,这种算法源于实型随机变量中普遍存在着的沿bit位以指数规律增强的均匀化趋势.任何实型的混沌序列,不论来自混沌映射系统还是混沌微分动力系统,都可以在同一个标准算法下变换成均匀分布的伪随机序列,因而是混沌伪随机数发生器标准化模块设计和硬件实现的关键技术基础. 关键词： 混沌 伪随机序列 均匀分布函数     

混沌时间序列的自适应高阶非线性滤波预测

根据混沌序列产生的确定性和非线性机制,基于Volterra级数展式和混沌序列高阶奇异谱特征,提出了一种高阶非线性傅里叶红外(HONFIR)滤波预测模型用于混沌时间序列的自适应预测.其自适应算法采用时域正交算法来自适应地跟踪混沌的运动轨迹,而不是重构混沌系统 的全局或局部运动轨迹.实验研究表明：(1)这种HONFIR自适应滤波器能够有效地预测一些超 混沌序列.(2)预测混沌序列的性能与预测模型的非线性拟合能力有关,但并非非线性程度越 高,预测性能就越好.(3)当HONFIR滤波器对混沌序列的非线性拟合精度高时,其自适应预测 的性能与其输入维数的关系不受Takens嵌入定理的约束.(4)HONFIR自适应滤波器具有一定的 抗噪能力. 关键词： 混沌 非线性模型 滤波器     

A universal algorithm to generate pseudo-random numbers based on uniform mapping as homeomorphism

A specific uniform map is constructed as a homeomorphism mapping chaotic time series into [0,1] to obtain sequences of standard uniform distribution. With the uniform map, a chaotic orbit and a sequence orbit obtained are topologically equivalent to each other so the map can preserve the most dynamic properties of chaotic systems such as permutation entropy. Based on the uniform map, a universal algorithm to generate pseudo random numbers is proposed and the pseudo random series is tested to follow the standard 0-1 random distribution both theoretically and experimentally. The algorithm is not complex, which does not impose high requirement on computer hard ware and thus computation speed is fast. The method not only extends the parameter spaces but also avoids the drawback of small function space caused by constraints on chaotic maps used to generate pseudo random numbers. The algorithm can be applied to any chaotic system and can produce pseudo random sequence of high quality, thus can be a good universal pseudo random number generator.     

基于强度统计算法的混沌序列复杂度分析

为了分析混沌序列的复杂度,文中采用强度统计复杂度算法分别对离散混沌系统(TD-ERCS)和连续混沌系统(简化Lorenz系统)进行复杂度分析,计算了混沌序列随参数变化的复杂度,分析了连续混沌系统产生的伪随机序列分别进行m序列和混沌伪随机序列扰动后的复杂度.研究表明,强度统计复杂度算法是一种有效的复杂度分析方法,离散混沌序列复杂度大于连续混沌序列复杂度,但对连续混沌系统的伪随机序列进行m序列和混沌伪随机序列扰动后可大大增加复杂度,为混沌序列在信息加密中的应用提供了理论依据. 关键词： 强度统计复杂度算法 TD-ERCS系统 简化Lorenz系统 序列扰动     

A novel algorithm to analyze the dynamics of digital chaotic maps in finite-precision domain

Chaotic maps are widely used to design pseudo-random sequence generators, chaotic ciphers, and secure communication systems. Nevertheless, the dynamic characteristics of digital chaos in finite-precision domain must be degraded in varying degrees due to the limited calculation accuracy of hardware equipment. To assess the dynamic properties of digital chaos, we design a periodic cycle location algorithm (PCLA) from a new perspective to analyze the dynamic degradation of digital chaos. The PCLA can divide the state-mapping graph of digital chaos into several connected subgraphs for the purpose of locating all fixed points and periodic limit cycles contained in a digital chaotic map. To test the versatility and availability of our proposed algorithm, the periodic distribution and security of 1-D logistic maps and 2-D Baker maps are analyzed in detail. Moreover, this algorithm is helpful to the design of anti-degradation algorithms for digital chaotic dynamics. These related studies can promote the application of chaos in engineering practice.