Monte Carlo simulation of electric conductivity for pure and doping fullerene (C60)

In this paper, we have used Monte Carlo (MC) method to simulate and study the temperature and doping effects on the electric conductivity of fullerene (C60). The results show that the band gap has reduced by the doping and the charge carrier transport is facilitated from valence band to conduction band by the temperature where is touched a 300 K. In this case, the conductivity reached a value of $4\times {10}^{-7}\text{S}{\text{cm}}^{-1}$. The electric conductivity of C60 can increase by the triphenylmethane dye crystal violet (CV) alkali metal to reach $4\times {10}^{-3}\text{S}{\text{cm}}^{-1}$ at 303 K. Our results of MC simulation have a good agreement with those extracted from literature [10], [33].     

基于矢量平均的信道估计算法

提出一种适用于DS-CDMA无线通信系统的低计算量而性能良好的信道估计算法。在DS-CDMA系统中，当接收信号经过解扩或多用户检测等时域预处理后，可以认为干扰大大减弱、期望信号在处理后的信号中占主要地位。这样，用预处理后信号相关阵的最大特征值对应的特征矢量可以很好地近似期望信号的信道矢量。但是，直接特征分解需要很大的计算量，特征跟踪计算量较低，但瞬态性能较差。本文提出一种基于相关矩阵列矢量平均的信道估计算法，该算法不需要特征分解或跟踪。仿真结果表明：新算法在降低计算量的情况下可以获得同直接特征分解方法几乎相同的性能。     

Kalman filtering of a space-time Markov random field

In this paper, finite-dimensional recursive filters for space-time Markov random fields are derived. These filters can be used with the expectation maximization (EM) algorithm to yield maximum likelihood estimates of the parameters of the model.     

Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at     

Non-universal critical behaviour of heteronuclear dimers on a square lattice––A Monte Carlo study

Monte Carlo simulation within the grand canonical ensemble, the histogram reweighting technique, and finite size scaling analysis are used to explore the phase behaviour of heteronuclear dimers, composed of A and B type atoms, on a square lattice. We have found that for the models with attractive BB and AB nearest-neighbour energy, u_BB=u_AB=−1, and for non-repulsive energy between AA nearest-neighbour sites, u_AA<0, the system belongs to the universality class of the two-dimensional Ising model. However, when u_AA>0, the system exhibits a non-universal critical behaviour. We have evaluated the dependences of the critical point characteristics on the value of u_AA.     

Approximation of photonuclear interaction cross-sections

Photonuclear interaction cross-sections from the GEANT4 database are approximated for all nuclei and all energies (from the hadron production threshold to about 40 TeV). The approximation methods in the giant-dipole resonance region, nucleon resonance region, and high-energy region are improved with respect to existing approximations. As an application of the approximation for photonuclear cross-sections, an improved method of calculating electronuclear cross-sections is developed. The interaction cross-section of virtual photons with nuclei at high Q² are approximated and a simple algorithm for describing the electronuclear reactions, including high-Q² scattering, is proposed. Received: 22 February 2002 / Accepted: 6 May 2002     

Construction algorithms for polynomial lattice rules for multivariate integration

We introduce a new construction algorithm for digital nets for integration in certain weighted tensor product Hilbert spaces. The first weighted Hilbert space we consider is based on Walsh functions. Dick and Pillichshammer calculated the worst-case error for integration using digital nets for this space. Here we extend this result to a special construction method for digital nets based on polynomials over finite fields. This result allows us to find polynomials which yield a small worst-case error by computer search. We prove an upper bound on the worst-case error for digital nets obtained by such a search algorithm which shows that the convergence rate is best possible and that strong tractability holds under some condition on the weights.

We extend the results for the weighted Hilbert space based on Walsh functions to weighted Sobolev spaces. In this case we use randomly digitally shifted digital nets. The construction principle is the same as before, only the worst-case error is slightly different. Again digital nets obtained from our search algorithm yield a worst-case error achieving the optimal rate of convergence and as before strong tractability holds under some condition on the weights. These results show that such a construction of digital nets yields the until now best known results of this kind and that our construction methods are comparable to the construction methods known for lattice rules.

We conclude the article with numerical results comparing the expected worst-case error for randomly digitally shifted digital nets with those for randomly shifted lattice rules.

     

Tomographic reconstruction using heuristic Monte Carlo methods

A tomographic reconstruction method based on Monte Carlo random searching guided by the information contained in the projections of radiographed objects is presented. In order to solve the optimization problem, a multiscale algorithm is proposed to reduce computation. The reconstruction is performed in a coarse-to-fine multigrid scale that initializes each resolution level with the reconstruction of the previous coarser level, which substantially improves the performance. The method was applied to a real case reconstructing the internal structure of a small metallic object with internal components, showing excellent results.     

Methods for implementing the stream boundary condition in DSMC computations

In the direct simulation Monte‐Carlo (DSMC) method for simulating rarefied gas flows, the velocities of simulator particles that cross a simulation boundary and enter the simulation space are typically generated using the acceptance–rejection procedure that samples the velocities from a truncated theoretical velocity distribution that excludes low and high velocities. This paper analyses an alternative technique, where the velocities of entering particles are obtained by extending the simulation procedures to a region adjacent to the simulation space, and considering the movement of particles generated within that region during the simulation time step. The alternative method may be considered as a form of acceptance–rejection procedure, and permits the generation of all possible velocities, although the population of high velocities is depleted with respect to the theoretical distribution. Nevertheless, this is an improvement over the standard acceptance–rejection method. Previous implementations of the alternative method gave a number flux lower than the theoretical number required. Two methods for obtaining the correct number flux are presented. For upstream boundaries in high‐speed flows, the alternative method is more computationally efficient than the acceptance–rejection method. However, for downstream boundaries, the alternative method is extremely inefficient. The alternative method, with the correct theoretical number flux, should therefore be used in DSMC computations in favour of the acceptance–rejection method for upstream boundaries in high‐speed flows. Copyright © 2003 John Wiley & Sons, Ltd.     

红外目标精跟踪方法的研究

本文提出了一种直接把红外前视传感器的输出作为测量值来跟踪红外目标的扩展型卡尔曼滤波跟踪算法。在滤波处理时,设置可变的测量矩阵,其目的在于提高运算速度和抑制噪声干扰。通过具体的实例,对所提跟踪算法的特点和有效性进行了细致的分析。