基于广义窗函数和最小二乘支持向量机的混沌背景下微弱信号检测

为了从混沌背景中检测微弱信号,研究分析了复杂非线性系统的相空间重构理论,提出了一种基于广义窗函数的最小二乘支持向量机的预测法. 该方法以广义嵌入窗为基础,利用自关联函数法确定Lorenz系统的嵌入维数和时间延迟, 实现相空间重构,结合最小二乘支持向量机建立Lorenz系统的误差预测模型, 检测微弱目标信号(瞬态和周期信号).仿真实验表明,该方法的预测模型具有较小的误差, 能够有效地从混沌背景噪声中检测出微弱目标信号,减小噪声对目标信号的影响. 与传统方法相比,在降低检测门限的同时,能够有效地提高预测的精度, 在混沌噪声下信噪比为-87.41 dB的情况下,相对于传统支持向量机方法所得的均方根误差0.049(-54.60 dB时)降低近两个数量级至0.000036123(-87.41 dB时).     

面向全光物理随机数发生器的混沌实时光采样研究

基于混沌激光实现全光物理随机数发生器的物理基础是完成对混沌光信号的高速实时全光采样. 本文利用偏振无关的SOA构建出TOAD全光采样门, 以光反馈半导体激光器产生混沌激光, 对混沌激光的全光采样可行性进行了原理性实验论证, 实现了对光反馈半导体激光器产生的6.4 GHz带宽的混沌激光5 GSa/s的实时、高保真全光采样. 进一步研究显示, 光采样周期与外腔反馈时间成比例与否对混沌信号弱周期性的抑制水平影响显著. 当两者不成比例时, 可有效消除原始混沌信号的弱周期性, 有利于高质量物理随机数的产生.     

Improvement of signal-to-noise ratio in chaotic laser radar based on algorithm implementation

Chaotic laser radar based on correlation detection is a high-resolution measurement tool for remotely monitoring targets or objects.However,its effective range is often limited by the side-lobe noise of correlation trace,which is always increased by the randomness of the chaotic signal itself and other transmission channel noises or interferences.The experimental result indicates that the wavelet denoising method can recover the real chaotic lidar signal in strong period noise disturbance,and a signal-to-noise ratio of about 8 dB is increased.Moreover,the correlation average discrete-component elimination algorithm significantly suppresses the side-lobe noise of the correlation trace when 20 dB of chaotic noise is embedded into the chaotic probe signal.Both methods have advantages and disadvantages.     

混沌背景下信号的盲分离

混沌信号与确定性小信号叠加生成的混合信号是一更高维的混沌信号,因而不能用一般的混沌信号噪声抑制的方法进行分离.提出了一种这类信号盲分离的方法.在重构未知的混沌信号的动力方程时,充分利用混沌吸引子的几何特性,并且限定动力映射为原混沌吸引子所在流形的内部映射,从而保证了重构的动力系统方程对应于原混沌信号,而不是同样具有混沌特性的混合信号.然后利用重构的动力方程,借用混沌信号中的噪声抑制思想,估计出原混沌信号对应的轨道,实现信号分离.通过对Lorenz系统中谐波信号、Henon映象中自回归过程,以及脑电信号中谐波信号进行提取的数值实验,验证了信号盲分离方法的有效性和可行性. 关键词： 混沌 非线性 信号处理 盲分离     

Adaptive strategies for recognition,noise filtering,control, synchronization and targeting of chaos

Combining knowledge of the local variation rates with some information on the long time trends of a dynamical system, we introduce an adaptive recognition technique consisting in a sequence of variable resolution observation intervals at which the geometrical positions are sampled. The sampling times are chosen so that the sequence of observed points forms a regularized set, in the sense that the separation of adjacent points is almost uniform. We show how this adaptive technique is able to recognize the unstable periodic orbits embedded within a chaotic attractor and stabilize anyone of them even in the presence of noise, through small additive corrections to the dynamics. These techniques have been applied to the synchronization of three chaotic systems, assuring secure communication between a message sender and a message receiver; furthermore they provide robust solutions to the problems of targeting of chaos and of filtering the noise out of an experimental chaotic data set. Implementation of adaptive methods to chaotic Lorenz, three and four dimensional Roessler models and Mackey-Glass delayed system are reported.(c) 1997 American Institute of Physics.     

Instability control in microwave-frequency microplasma

This paper introduces comprehensive large-signal analyses of modulation dynamics and noise of a chaotic semiconductor laser. The chaos is induced by operating the laser under optical feedback (OFB). Control of the chaotic dynamics and possibility of suppressing the associated noise by sinusoidal modulation are investigated. The studies are based on numerical solutions of a time-delay rate equation model. The deterministic modulation dynamics of the laser are classified into seven regular and irregular dynamic types. Variations of chaotic dynamics and noise with sinusoidal modulation are examined in both time and frequency domains over wide ranges of the modulation depth and frequency. The results showed that chaotic dynamics can be converted into five distinct dynamic types; namely, continuous periodic signal (CPS), continuous periodic signal with relaxation oscillations (CPSRO), periodic pulse (PP), periodic pulse with relaxation oscillations (PPRO) and periodic pulse with period doubling (PPPD). The relative intensity noise (RIN) of these types is characterized when the modulation frequencies are much lower, comparable to, and higher than the resonance frequency. Suppression of RIN to a level 8 dB/Hz higher than the quantum limit was predicted under the CPS type when the modulation frequency is 0.9 times the resonance frequency and the modulation depth is 0.14.     

金属互连电迁移噪声的相关维数研究

针对金属铝互连中噪声信号随电迁移过程变化规律及其所反映的内部失效机理问题，提出将相关维数用于对电迁移噪声时间序列的分析.通过对互连电迁移噪声实验数据的相关维数计算，发现随着电迁移的进行，金属铝互连噪声由随机性成分占主导变为确定性成分占主导，反映出噪声由随机信号转变为混沌动力学信号.应用散射理论解释上述现象，在金属互连电迁移中，空位扩散阶段噪声主要产生机制是空位随机散射；在空位聚集到空洞成核这一过程中，噪声产生机制逐渐从随机散射转变到弹道混沌腔输运机制为主.通过与传统表征参量的对比，证明相关维数可用于预测金 关键词： 电迁移 噪声 相关维数 混沌     

一种混沌海杂波背景下的微弱信号检测方法

基于复杂非线性系统的相空间重构理论,提出了一种基于遗传算法的支持向量机预测方法.利用改进的自相关法和饱和关联维数法确定混沌信号的时间延迟和嵌入维,从而实现相空间重构.通过遗传算法优化支持向量机中的惩罚系数和核函数参数,并结合支持向量机建立混沌序列的单步预测模型,从预测误差中检测出淹没在混沌背景中的微弱信号(包括瞬态信号和周期信号).以Lorenz系统和加拿大McMaster大学利用IPIX雷达实测得到的海杂波数据作为混沌背景噪声进行仿真实验,结果表明该方法能够有效地从混沌背景噪声中检测出微弱目标信号,所得的均方根误差为0.00049521(信噪比为-89.7704 dB),这比传统支持向量机方法的均方根误差(0.049,信噪比为-54.60 dB)降低了两个数量级.     

基于小波变换的混沌信号相空间重构研究

应用小波变换和非线性动力学方法研究了混沌信号在相空间中的行为，指出混沌时间序 列的小波变换实质上是在重构的相空间中，混沌吸引子向小波滤波器向量所张的空间中的投 影，与Packard等人提出的相空间重构方法本质上是一致的.实验结果表明，混沌信号经过 小波变换后，吸引子轨迹与原有轨迹具有相似的结构，同时，系统的关联维数、Kolmogorov 熵等非线性不变量仍然得到保留.这些结果表明，利用小波变换研究混沌信号是有效的. 关键词： 小波变换 相空间重构 混沌信号 脑电信号     

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.     

利用小波多尺度分解算法实现混沌系统的噪声减缩

应用小波多尺度分解算法进行噪声减缩,从混沌背景中分离周期信号、噪声及其他混沌信号.小波多尺度分解算法能够区分不同尺度的信号是利用小波变换在时、频两域具有突出信号特征的能力以及小波变换是一线性变换的特点.提出的方法仅利用信号的尺度特性,克服了先前的噪声减缩要知道产生混沌信号的数学模型,并且要求叠加在混沌背景中的其他信号的幅度相对混沌背景信号的幅度很小的假定.给出了从Lorenz混沌背景中提取正弦信号、白噪声和Chua's电路产生的混沌信号的计算机模拟结果. 关键词：     

Chaos in brake squeal noise

Brake squeal has become an increasing concern to the automotive industry because of warranty costs and the requirement for continued interior vehicle noise reduction. Most research has been directed to either analytical and experimental studies of brake squeal mechanisms or the prediction of brake squeal propensity using finite element methods. By comparison, there is a lack of systematic analysis of brake squeal data obtained from a noise dynamometer. It is well known that brake squeal is a nonlinear transient phenomenon and a number of studies using analytical and experimental models of brake systems (e.g., pin-on-disc) indicate that it could be treated as a chaotic phenomenon. Data obtained from a full brake system on a noise dynamometer were examined with nonlinear analysis techniques. The application of recurrence plots reveals chaotic structures even in noisy data from the squealing events. By separating the time series into different regimes, lower dimensional attractors are isolated and quantified by dynamic invariants such as correlation dimension estimates or Lyapunov exponents. Further analysis of the recurrence plot of squealing events by means of recurrence quantification analysis measures reveals different regimes of laminar and random behaviour, periodicity and chaos-forming recurrent transitions. These results help to classify brake squeal mechanisms and to enhance understanding of friction-related noise phenomena.     

混沌信号自适应协同滤波去噪

混沌信号协同滤波去噪算法充分利用了混沌信号的自相似结构特征,具有良好的信噪比提升性能.针对该算法的滤波参数优化问题,考虑到最优滤波参数的选取受到信号特征、采样频率和噪声水平的影响,为提高该算法的自适应性使其更符合实际应用需求,基于排列熵提出一种滤波参数自动优化准则.依据不同噪声水平的混沌信号排列熵的不同,首先选取不同滤波参数对含噪混沌信号进行去噪,然后计算各滤波参数对应重构信号的排列熵,最后通过比较各重构信号的排列熵,选取排列熵最小的重构信号对应的滤波参数为最优滤波参数,实现滤波参数的优化.分析了不同信号特征、采样频率和噪声水平情况下滤波参数的选取规律.仿真结果表明,该参数优化准则能在不同条件下对滤波参数进行有效的自动最优化,提高了混沌信号协同滤波去噪算法的自适应性.     

变尺度概率净化法的优化

变尺度概率净化法是一种混沌时间序列非线性动力学降噪方法，该方法需对整个相空间点列做联合处理，因此算法的计算量和所需内存量会随着每个轨道点的修正参考点数和嵌入维数的增加而呈指数增长.根据变尺度概率净化法的特点，对前向概率和转移概率的估计方法作了一些改进，使算法的运算量减小到了原来的0.27左右，而降噪性能并没有下降，并提出了数据较长情况下的算法实现结构，大大降低了算法运行所需内存. 关键词： 混沌 非线性动力学 降噪 最大后验概率估计 变尺度概率净化     

Detecting variation in chaotic attractors

If the output of an experiment is a chaotic signal, it may be useful to detect small changes in the signal, but there are a limited number of ways to compare signals from chaotic systems, and most known methods are not robust in the presence of noise. One may calculate dimension or Lyapunov exponents from the signal, or construct a synchronizing model, but all of these are only useful in low noise situations. I introduce a method for detecting small variations in a chaotic attractor based on directly calculating the difference between vector fields in phase space. The differences are found by comparing close strands in phase space, rather than close neighbors. The use of strands makes the method more robust to noise and more sensitive to small attractor differences.     

Cubic映象的瞄准与控制

实现了沿参数轴对不稳定周期轨道的连续控制,通过同时应用调节参数与变量微扰可实现对混沌区与分岔区中任一点的瞄准。给出的方法具有抗干扰性     

基于参数非共振激励混沌抑制原理的微弱方波信号检测

利用自治混沌系统的参数非共振激励混沌抑制原理实现强噪声背景下微弱方波信号的检测. 将频率远大于系统特征频率的方波信号作为内置激励信号，经平均法处理后，得到受控系统与原系统之间的参数等效关系，并由此确定使系统由混沌状态突变为周期状态的检测参数临界值. 数值仿真结果表明此系统可以达到极低的信噪比工作下限. 相比于利用参数共振微扰混沌抑制原理实现微弱信号检测的有关方法，此方案可根据严格的理论分析得到更准确的检测参数估计值，有利于在相关领域推广应用. 关键词： 自治混沌系统 参数激励 方波信号 检测     

Low frequency oscillations in semi-insulating GaAs: a nonlinear analysis

We have observed low frequency current oscillations in a semi-insulating GaAs sample grown by low temperature molecular beam epitaxy. For this, an experimental setup proper to measure high impedance samples with small external noise was developed. Spontaneous oscillations in the current were observed for some bias conditions. Although measurements were carried out from room temperature down to liquid helium, the dynamical analysis was carried out around 200 K where the signal to noise ratio was fairly favorable. To increase the data quality we have also used a noise reduction algorithm suitably developed for nonlinear systems. We observed attractors having low embedding dimension, limit cycle bifurcations, and chaotic behavior characteristic of nonlinear dynamical processes in route to chaos. Attractor reconstruction, Poincare sections, Lyapunov exponents, and correlation dimension were also analyzed.     

Controlling chaos in a high dimensional system with periodic parametric perturbations

The effect of applying a periodic perturbation to an accessible parameter of a high-dimensional (coupled-Lorenz) chaotic system is examined. Numerical results indicate that perturbation frequencies near the natural frequencies of the unstable periodic orbits of the chaotic system can result in limit cycles or significantly reduced dimension for relatively small perturbations.