Initial data truncation for multivariate output of discrete-event simulations using the Kalman filter

Data truncation is a commonly accepted method of dealing with initialization bias in discrete-event simulation. An algorithm for determining the appropriate initial-data truncation point for multivariate output is proposed. The technique entails averaging across independent replications and estimating a steady-state output model in a state-space framework. A Bayesian technique called Multiple Model Adaptive Estimation (MMAE) is applied to compute a time varying estimate of the output's steady-state mean vector. This MMAE implementation features the use, in paralle, of a bank of Kalman filters. Each filter is constructed under a different assumption concerning the output's steady-state mean vector. One of the filters assumes that the steady-state mean vector is accurately reflected by an estimate, called the assumed steady-state mean vector, taken from the last half of the simulation data. As the filters process the output through the effective transient, this particular filter becomes more likely (in a Bayesian sense) to be the best filter to represent the data and the MMAE mean estimator is influenced increasingly towards the assumed steady-state mean vector. The estimated truncation point is selected when a norm of the MMAE mean vector estimate is within a small tolerance of the assumed steady-state mean vector. A Monte Carlo analysis using data from simulations of open and closed queueing models is used to evaluate the technique. The evaluation criteria include the ability to construct accurate and reliable confidence regions for the mean response vector based on the truncated sequences.     

Dynamic complexity of optimal paths and discount factors for strongly concave problems

We study the relationship between the dynamical complexity of optimal paths and the discount factor in general infinite-horizon discrete-time concave problems. Given a dynamic systemx _t+1=h(x _t ), defined on the state space, we find two discount factors 0 < ^{* **} < 1 having the following properties. For any fixed discount factor 0 < < ^*, the dynamic system is the solution to some concave problem. For any discount factor ^** < < 1, the dynamic system is not the solution to any strongly concave problem. We prove that the upper bound ^** is a decreasing function of the topological entropy of the dynamic system. Different upper bounds are also discussed.This research was partially supported by MURST, National Group on Nonlinear dynamics in Economics and Social Sciences. The author would like to thank two anonymous referees for helpful comments and suggestions.     

光子晶体反常色散超窄带滤波理论

讨论了利用由反常色散材料构成的二维（2D）光子晶体(PCs)实现超窄带滤波（PCADOF）的原理，并对铯原子蒸气6P3/2←6S1/2谱线的反常色散曲线进行了研究，讨论利用此反常色散曲线通过2D PCs实现超窄带滤波的方法和特点，研究发现这种滤光器的带宽可达到0.002nm，这将为设计一种全新的滤波器提供指导. 关键词： 反常色散 光子晶体 超窄带滤波     

基于科赫曲线分形结构太赫兹带通滤波器

太赫兹滤波器是太赫兹通信、太赫兹成像和太赫兹检测等太赫兹应用系统中不可或缺的功能器件。按照不同的分类方式,滤波器有不同的种类,常见的按照选频功能可分为高通滤波器、低通滤波器、带阻滤波器和带通滤波器。为了实现在太赫兹波段的滤波效果,世界各地的研究人员利用不同的结构、材料和控制方式实现了功能各异的太赫兹滤波器,但是考虑到设计的器件要应用到太赫兹系统中,成本低廉、结构简单、性能优越的太赫兹滤波器一直是研究人员的追求。分形概念自提出以来在很多研究领域都有了快速发展,但是在太赫兹波段的应用还不是很常见,特别是应用于太赫兹功能器件的设计。引入分形中科赫曲线的概念设计并制备了一种新型的太赫兹带通滤波器,该滤波器是在金属薄膜上刻蚀出科赫曲线分形结构,当太赫兹波垂直入射到该滤波器时候实现了在太赫兹波段的窄带滤波。在滤波器的设计过程中,追求理论与实验相结合,首先在电磁仿真软件中建立科赫曲线分形结构滤波器模型进行计算,探究分形结构应用于太赫兹波段进行滤波的可行性,在进行多次计算之后得到优化后的尺寸和结构,然后根据优化后的尺寸加工出科赫曲线分形结构太赫兹滤波器样品,并且将样品放在太赫兹时域光谱系统中进行实验测量,得到实验数据后与仿真结果进行比较。在仿真中利用了时域有限差分法模拟科赫曲线分形结构太赫兹带通滤波器的传输特性,优化后的仿真结果表明:滤波器的谐振频率为0.715 THz,透射系数能够达到0.92,-3 dB带宽为21.9 GHz,将仿真得到的散射参数进行S参数反演得到了太赫兹滤波器样品的电磁参数,这在理论上分析了太赫兹波在谐振点处产生透射增强的原因。利用飞秒激光微加工系统制备了尺寸优化后的科赫曲线分形结构太赫兹带通滤波器样品,然后使用太赫兹时域光谱系统对样品的传输特性进行测试,对实验得到的时域数据进行快速傅里叶变换之后得到频域数据,再把频域数据进行归一化处理后与之前的电磁仿真结果进行对比,发现实验测得的结果与电磁软件仿真得到的结果较为吻合。     

基于EKF的水下LD通信精对准控制算法

高速激光通信中接收机与光斑中心很难处于精对准状态,导致水下光通信链路难以稳定建立.首先采用蒙特卡洛仿真统计法分析激光光子在海水中传输的接收光强分布规律,再通过实验对接收端的光斑图像进行采样分析,利用曲线拟合得到接收器位置与接收光强的关系.仿真与实验结果表明:光束经过25 m的水下传输,接收光强分布仍近似为高斯分布.采用非线性估计算法(扩展卡尔曼滤波)与基本状态控制反馈理论,根据接收光强度估计接收器当前位置与最大光强处的距离,通过反馈算法实现接收端与光斑中心的主动跟踪对准.算法仿真结果显示,接收端对准误差在2 mm以下,稳定后接收效率超过98%.     

Transition probabilities of the X1Σ+, A1Π, B1Δ, C1Σ+, and D1Π states of the AlO+ cation

ABSTRACT

This study computes the potential energy curves of the X¹Σ⁺, A¹Π, B¹Δ, C¹Σ⁺, and D¹Π states of AlO⁺ cation and the transition dipole moments between them. The orders of the rotationless radiative lifetimes are 10–100?μs for the A¹Π state, 1–1000?ms for the B¹Δ state, 10?ns for the first well and 100?ns for the second well of the C¹Σ⁺ state, and 1?μs for the D¹Π state. Emissions of the B¹Δ–A¹Π and D¹Π–C¹Σ⁺ systems are so weak that they are hardly measured via spectroscopy, the emissions of the C¹Σ⁺–X¹Σ⁺, C¹Σ⁺–A¹Π, and D¹Π–X¹Σ⁺ systems are so strong that they can be detected readily, and emissions of the A¹Π–X¹Σ⁺ and D¹Π–A¹Π systems can be observed through spectroscopy only by a significant effort. There is a strong great similarity between spontaneous emissions of the A¹Π–X¹Σ⁺ system of the AlO⁺ cation and the A²Π–X²Σ⁺ system of the AlO radical. The emissions of the A²Π–X²Σ⁺ system of the AlO radical have been measured in outer space Therefore, it is highly possible that the emissions of the A¹Π–X¹Σ⁺ system of the AlO⁺ cation can be detected in the astrophysical media.     

Synthesis of bandpass grid filter for linear polarized millimeter wave

A method based on equivalent circuit and transmission line model is proposed to design narrow bandpass grid filters in short millimeter wave. Several bandpass filters with 2, 3 or 4 element inductive wire grids in the 70GHz region have been designed with Butterworth or Chebyshev characteristic for linear polarized wave. The agreement between measurement and design theory is good and this proves the rationality and practicality of our design theory.     

基于粒子滤波的运动目标光电定位仿真研究

运动目标的光电定位不能像静止目标那样简单做均值滤波,鉴于此,引入粒子滤波算法,它不仅可以应用于线性系统,而且还适用于非线性系统。结合光电定位需求,详细推导了计算公式及初值和参数选取公式,对只含测量噪声以及含有测量和运动噪声等的海面运动目标光电无源定位算法进行了仿真计算,验证了算法的有效性,讨论了噪声强度对滤波效果的影响,滤波参数选择对滤波效果的影响,目标运动方式对滤波跟随性的影响,重采样算法对滤波效果的影响等。所得结论为:粒子滤波可用于运动目标光电定位过程,可有效降低定位误差;粒子滤波算法具有较强鲁棒性,适用于噪声较大、目标运动形态变化大等情况。     

Design of diamond-shape photonic crystal fiber polarization filter based on surface plasma resonance effect

A novel plasmonic polarization filter based on the diamond-shape photonic crystal fiber(PCF) is proposed. The resonant coupling characteristics of the PCF polarization filter are investigated by the full-vector finite-element method. By optimizing the geometric parameters of the PCF, when the fiber length is 5 mm, the polarization filter has a bandwidth of 990 nm and an extinction ratio(ER) of lower than -20 dB. Moreover, a single wavelength polarization filter can also be achieved, along with an ER of -279.78 dB at wavelength 1.55 μm. It is believed that the proposed PCF polarization filter will be very useful in laser and optical communication systems.     

An Improved Composite Multiscale Fuzzy Entropy for Feature Extraction of MI-EEG

Motor Imagery Electroencephalography (MI-EEG) has shown good prospects in neurorehabilitation, and the entropy-based nonlinear dynamic methods have been successfully applied to feature extraction of MI-EEG. Especially based on Multiscale Fuzzy Entropy (MFE), the fuzzy entropies of the τ coarse-grained sequences in τ scale are calculated and averaged to develop the Composite MFE (CMFE) with more feature information. However, the coarse-grained process fails to match the nonstationary characteristic of MI-EEG by a mean filtering algorithm. In this paper, CMFE is improved by assigning the different weight factors to the different sample points in the coarse-grained process, i.e., using the weighted mean filters instead of the original mean filters, which is conductive to signal filtering and feature extraction, and the resulting personalized Weighted CMFE (WCMFE) is more suitable to represent the nonstationary MI-EEG for different subjects. All the WCMFEs of multi-channel MI-EEG are fused in serial to construct the feature vector, which is evaluated by a back-propagation neural network. Based on a public dataset, extensive experiments are conducted, yielding a relatively higher classification accuracy by WCMFE, and the statistical significance is examined by two-sample t-test. The results suggest that WCMFE is superior to the other entropy-based and traditional feature extraction methods.