An Integral Algorithm for Numerical Integration of One-Dimensional Additive Colored Noise Problems

We present an integral-closed algorithm for solving a Langevin equation driven by an additive colored noise. Both the mean first passage time in a bistable system and the diffusion current in a titled periodic potential are calculated and the comparison with existing algorithms is carried out. The dependence of the numerical results on the time steps is studied. Our algorithm is shown to have high accuracy and stability.     

Global Pressure of One-Dimensional Polydisperse Granular Gases Driven by Gaussian White Noise

We study the global pressure of a one-dimensional polydisperse granular gases system for the first time, in which the size distribution of particles has the fractal characteristic and the inhomogeneity is described by a fractal dimension D. The particles are driven by Gaussian white noise and subject to inelastic mutual collisions. We define the global pressure P of the system as the impulse transferred across a surface in a unit of time, which has two contributions, one from the translational motion of particles and the other from the collisions. Explicit expression for the global pressure in the steady state is derived. By molecular dynamics simulations, we investigate how the inelasticity of collisions and the inhomogeneity of the particles influence the global pressure. The simulation results indicate that the restitution coefficient e and the fractal dimension D have significant effect on the pressure.     

Global Pressure of One-Dimensional Polydisperse Granular Gases Driven by Gaussian White Noise

We study the global pressure of a one-dimensional polydisperse granular gases system for the first time,in which the size distribution of particles has the fractal characteristic and the inhomogeneity is described by a fractal dimension D. The particles are driven by Gaussian white noise and subject to inelastic mutual collisions. We define the global pressure P of the system as the impulse transferred across a surface in a unit of time, which has two contributions,one from the translational motion of particles and the other from the collisions. Explicit expression for the global pressure in the steady state is derived. By molecular dynamics simulations, we investigate how the inelasticity of collisions and the inhomogeneity of the particles influence the global pressure. The simulation results indicate that the restitution coefficient e and the fractal dimension D have significant effect on the pressure.     

随机噪声对激光陀螺输出特性的影响

分析了纯随机噪声输入和周期性抖动信号叠加随机噪声的复合抖动输入两种激励下，激光陀螺输出信号均值偏差和分散系数与随机噪声强度之间的数学关系，基于该关系公式，综合读出角速度标准差、输出信号均值偏差和分散系数，提出随机噪声强度的选择方法。研究表明，纯随机噪声减小频率闭锁影响没有应用价值，因为随机噪声的引入将导致激光陀螺测量范围的减小或输出方差的增大，这都不是理想的结果。而在周期性抖动信号基础上叠加随机噪声，并不影响激光陀螺的测量范围，却可大幅度地提高激光陀螺的读出精度，输出方差的增大可以通过延长采样周期予以减小，满足应用要求。     

Spectral Analysis of Stochastic Phase Lockings and Stochastic Bifurcations in the Sinusoidally Forced van der Pol Oscillator with Additive Noise

Noise effects on the phase lockings and bifurcations in the sinusoidally forced van der Pol relaxation oscillator are investigated. Deterministic (noise-free) one-dimensional Poincaré mapping is extended to the iteration of the operator defined by a stochastic kernel function. Stochastic phase lockings and bifurcations are analyzed in terms of the density evolution by the operator. In particular, a new method which uses spectra (eigenvalues and eigenfunctions) of the operator to analyze stochastic bifurcations intensively is proposed.     

四象限红外光电探测器噪声检测技术研究

分析了红外探测器的噪声组成与形成原因,针对多元探测器的特点,设计了低噪声多路切换开关电路,实现了噪声等效功率NEP的自动化测量,消除了电路中其他器件引入的噪声干扰。实验结果表明,本测量系统不仅具有较低的测量误差(≤2%),并且可以用于其他多元探测器的噪声检测。     

Implications of Noise on Neural Correlates of Consciousness: A Computational Analysis of Stochastic Systems of Mutually Connected Processes

Random fluctuations in neuronal processes may contribute to variability in perception and increase the information capacity of neuronal networks. Various sources of random processes have been characterized in the nervous system on different levels. However, in the context of neural correlates of consciousness, the robustness of mechanisms of conscious perception against inherent noise in neural dynamical systems is poorly understood. In this paper, a stochastic model is developed to study the implications of noise on dynamical systems that mimic neural correlates of consciousness. We computed power spectral densities and spectral entropy values for dynamical systems that contain a number of mutually connected processes. Interestingly, we found that spectral entropy decreases linearly as the number of processes within the system doubles. Further, power spectral density frequencies shift to higher values as system size increases, revealing an increasing impact of negative feedback loops and regulations on the dynamics of larger systems. Overall, our stochastic modeling and analysis results reveal that large dynamical systems of mutually connected and negatively regulated processes are more robust against inherent noise than small systems.     

Statistical Dynamics of Clustering in the Genome Structure

Clustering and long-range correlations in the nucleotide sequences of different categories of organisms are discussed. Clustering, mostly observed in higher eucaryotes, can be found at different length scales in DNA and Central Limit Theorems are used as links between these length scales. Several dynamical, statistical, mean-field models are proposed based on biologically motivated dynamical mechanisms and they successfully reproduce both the short range behavior observed in coding DNA and the long range, out-of-equilibrium features of non-coding DNA. Such dynamical mechanisms include aggregation of oligonucleotides, influx and DNA length reduction schemes, transpositions, and fusions of large DNA macromolecules. Fractality can be inferred from the short and long range correlations observed in the sequence structure of higher eucaryotes, where the non-coding part is relatively extended. In these organisms the DNA coding/non-coding alternation has the characteristics of finite size, fractal, random sets.     

随机粗糙微通道内流动特性研究

采用计算流体动力学的方法, 研究了微通道内气体在速度滑移和随机表面粗糙度耦合作用下的流动特性. 其中, 利用二阶速度滑移边界条件描述气体的边界滑移, 利用分形几何学建立随机粗糙表面. 研究发现, 综合考虑二阶速度滑移边界条件和随机表面粗糙度在较大的平均Knudsen数范围内 (0.025-0.59) 得到的计算结果与实验数据符合得很好, 而一阶速度滑移边界条件只在平均Knudsen数较小时(<0.1)符合实验结果. 随机表面粗糙度对气体在边界处的滑移有显著影响, 相对粗糙度越大, 速度滑移系数越小. 并针对计算结果, 给出了滑移系数与相对粗糙度近似满足的关系. 随机粗糙表面对气体流动过程中的压强、速度、Poiseuille数也有显著影响. 关键词： 随机表面粗糙度 二阶速度滑移边界条件 分形 微通道     

具有频率噪声的单模激光线性模型随机共振

将频率有涨落的周期信号输入单模激光增益模型,计算出输出光强的相关函数及功率谱,对信噪比随噪声强度和系统参数的变化进行了研究. 结果表明:信噪比随频率噪声强度的变化、抽运噪声强度的变化、量子噪声强度的变化均出现随机共振;信噪比随增益系数和损失系数的变化也出现随机共振. 关键词： 频率噪声 功率谱 随机共振     

基于改进的压缩式随机游走算法对静态电源/地网的模拟

将随机游走法和等效电路压缩相结合,对静态P/G网(Power and Ground Networks)进行分析.针对一个大规模的电路,在经过多层的参数提取和建模后,得到静态P/G网模型.首先根据网络的规律性,运用等效电路压缩法将原始的P/G网进行压缩处理,然后运用随机游走法求解,最后利用计算得到的化简网络电压值,通过相关的插值公式得到原网络的电压值.实验数据表明,改进的压缩式随机游走法可有效简化网络的复杂性,节省计算时间,计算速度提高到普通随机游走法的两个数量级以上.     

Classification of Random Image Fields Using Synthetic Discriminant Functions: Spectral Statistical Approach and Its Computer-Optical Realization

The problem of classification of images that have a perfectly random nature is considered. We propose a new approach to solve this problem that is based on the use of the synthetic discriminant functions being synthesized to separate linearly the power spectra of random image fields to be classified. In the stage of both discriminant function synthesis and classification, the statistical technique of power spectrum estimation is employed. The realization of the proposed approach by means of a hybrid computer-optical technique is discussed, and its efficiency is illustrated by two examples of real-world texture classification.     

不同响应波长的HgCdTe光导器件噪声分析

研究了不同响应波长的HgCdTe器件在不同背景辐射条件下的噪声变化.随着背景辐射的增加,甚长波器件的噪声减小,而中波器件相反.噪声频谱测量表明,产生-复合噪声分量和1/f噪声分量是器件的主要噪声来源,并且这两个分量随背景的变化趋势相同.非平衡载流子和器件有效寿命的理论分析,表明器件噪声随背景辐射的变化存在一个极大值,而中波和甚长波器件处在不同的作用区域内,接受到的背景辐射对载流子浓度和器件有效寿命的影响不同,从而噪声变化表现不同.在此基础上,提出了"临界背景通量密度"的概念.     

Steady-State Analysis of a Single-Mode Laser Driven by Colored Pump Noise with Cross-Correlation Between Real and Imaginary Parts of Quantum Noise

Applying the method of the unified colored noise approximation and phase lock, we study in this paper the stationary intensity distribution of the single-mode laser driven by colored pump noise with cross-correlation between the real and imaginary parts of the quantum noise. We present a thorough discussion of how the cross-correlation λq between the realand imaginary parts of the quantum noise and the self-correlation time τ of the pump noise determine the behaviors of the stationary distribution Qst(I), the mean (I), and the variance λ2(0) of the laser intensity. It is shown that cross-correlation intensity λq of the complex quantum noise can induce a first-order-like transition. When the pump noise is colored noise (τ≠ 0), improving the pump parameters monotonously will make the curves of Qst(I)exhibit reentrant phase transition. The fluctuations of laser intensity are strongly influenced by λq and τ when the laser is operated near or below threshold. Especially when τ≠ 0, the heights of the peaks of the curves of λ2(0)-a0 and λ3(0)-a0, (here a0 is the net gain coefficient) go up as λq increases. However the entire curves of λ2(0)-a0 and λ3(0)-a0are abruptly suppressed when λq = 1, in similarity to phase transition of stationary intensity distribution.     

Steady-State Analysis of a Single-Mode Laser Driven by Colored Pump Noise with Cross-Correlation Between Real and Imaginary Parts of Quantum Noise

Applying the method of the unified colored noise approximation and phase lock, we study in this paper the stationary intensity distribution of the single-mode laser driven by colored pump noise with cross-correlation between the real and imaginary parts of the quantum noise. We present a thorough discussion of how the cross-correlation λq between the real and imaginary parts of the quantum noise and the self-correlation time τ of the pump noise determine the behaviors of the stationary distribution Qst(I), the mean (I）, and the variance λ2(0) of the laser intensity. It is shown that cross-correlation intensity λq of the complex quantum noise can induce a first-order-like transition. When the pump noise is colored noise (τ≠0), improving the pump parameters monotonously will make the curves of Qst(I) exhibit reentrant phase transition. The fluctuations of laser intensity are strongly influenced by λq and τ when the laser is operated near or below threshold. Especially when τ≠0, the heights of the peaks of the curves of λ2(0)-α0 and α3(0)-α0, (here a0 is the net gain coefficient) go up as λq increases. However the entire curves λ2(0)-α0 and λ3(0)-α0 are abruptly suppressed when λq = 1, in similarity to phase transition of stationary intensity distribution.     

The Analysis of the Power Law Feature in Complex Networks

Consensus about the universality of the power law feature in complex networks is experiencing widespread challenges. In this paper, we propose a generic theoretical framework in order to examine the power law property. First, we study a class of birth-and-death networks that are more common than BA networks in the real world, and then we calculate their degree distributions; the results show that the tails of their degree distributions exhibit a distinct power law feature. Second, we suggest that in the real world two important factors—network size and node disappearance probability—will affect the analysis of power law characteristics in observation networks. Finally, we suggest that an effective way of detecting the power law property is to observe the asymptotic (limiting) behavior of the degree distribution within its effective intervals.     

Finite-Time Stochastic Stability Analysis of Permanent Magnet Synchronous Motors with Noise Perturbation

In this paper, we study the finite-time stability of permanent magnet synchronous motors (PMSMs) with noise perturbation. To eliminate the chaos in a PMSM and allow it to reach a steady state more quickly within a finite time, we propose a novel adaptive controller based on finite-time control theory. Finite-time stability implies optimal convergence time and better robustness. Finally, numerical simulations are performed to demonstrate the effectiveness and feasibility of our new results.     

结合卡尔曼滤波器噪声分析的车道线检测跟踪算法

使用卡尔曼滤波对视频序列图像中的具体信息进行跟踪的研究目前是跟踪方向的一个热点.但是在处理卡尔曼滤波跟踪过程中的过程噪声和测量噪声,大部分研究普遍采用的是初始赋值.通过不断的调整数,达到较好的跟踪效果.但是这样做不但没有遵循原始数据的规律,同时调整参数是一项耗时的工作.基于这个原因,提出了一种对卡尔曼滤波的过程噪声和测量噪声进行预估计的方法并将其应用到车道线跟踪过程中.通过对一部分离线数据进行处理,可以基本估计出系统的噪声参数.最后采用车道线跟踪算法对论文中的方法进行验证,实验证明,提出的参数估计方法在车道线的跟踪过程中达到很好的效果,同时处理每帧的时间为50ms左右,满足了实时性的要求.     

Motile parameters of cell migration in anisotropic environment derived by speed power spectrum fitting with double exponential decay

Cell migration through anisotropic microenvironment is critical to a wide variety of physiological and pathological processes.However,adequate analytical tools to derive motile parameters to characterize the anisotropic migration are lacking.Here,we proposed a method to obtain the four motile parameters of migration cells based on the anisotropic persistent random walk model which is described by two persistence times and two migration speeds at perpendicular directions.The key process is to calculate the velocity power spectra of cell migration along intrinsically perpendicular directions respectively,then to apply maximum likelihood estimation to derive the motile parameters from the power spectra fitting with double exponential decay.The simulation results show that the averaged persistence times and the corrected migration speeds can be good estimations for motile parameters of cell migration.     

自适应光学系统波前校正残余误差的功率谱分析方法

采用比较自适应光学系统闭环校正前后时间功率谱人方法,对自适应光学系统的波前校正残余误差进行了分析。在注意噪块时,实测的闭环波前复原相位误差与「实际波前校正残余误差是有区别的,分析了两者功率谱的差别之后,提出了一种估计实际波前校正残余误差的方法,应用这种方法对１．２米望远镜高分辨力自适应光学系统所采集的复原相位数据方差和波前校正残余误差进行了对比。