Nonstationary Markov chains and convergence of the annealing algorithm

We study the asymptotic behavior as timet + of certain nonstationary Markov chains, and prove the convergence of the annealing algorithm in Monte Carlo simulations. We find that in the limitt + , a nonstationary Markov chain may exhibit phase transitions. Nonstationary Markov chains in general, and the annealing algorithm in particular, lead to biased estimators for the expectation values of the process. We compute the leading terms in the bias and the variance of the sample-means estimator. We find that the annealing algorithm converges if the temperatureT(t) goes to zero no faster thanC/log(t/t ₀) ast+, with a computable constantC andt ₀ the initial time. The bias and the variance of the sample-means estimator in the annealing algorithm go to zero likeO(t^–1+) for some 0<1, with =0 only in very special circumstances. Our results concerning the convergence of the annealing algorithm, and the rate of convergence to zero of the bias and the variance of the sample-means estimator, provide a rigorous procedure for choosing the optimal annealing schedule. This optimal choice reflects the competition between two physical effects: (a) The adiabatic effect, whereby if the temperature is loweredtoo abruptly the system may end up not in a ground state but in a nearby metastable state, and (b) the super-cooling effect, whereby if the temperature is loweredtoo slowly the system will indeed approach the ground state(s) but may do so extremely slowly.     

Numerical comparison of several variable-metric algorithms

The paper compares the numerical performances of the LDL decomposition of the BFGS variable-metric algorithm, the Dennis-Mei dogleg algorithm on the BFGS update, and Davidon's projections with the BFGS update with the straight BFGS update on a number of standard test problems. Numerical results indicate that the standard BFGS algorithm is superior to all of the more complex strategies.This research was supported by the National Science Foundation under Research Grant No. MCS77-07327.     

The Enhancement of Efficiency of High-order Harmonic in Intense Laser Field Based on Asymptotic Boundary Conditions and Symplectic Algorithm

Asymptotic boundary condition (ABC) of laser-atom interaction presented recently is applied to transform the initial value problem of the time-dependent Schrödinger equation (TDSE) in infinite space into the initial and boundary value problem in the finite space, and then the TDSE is discretized into linear canonical equations by substituting the symmetry difference quotient for the 2-order partial derivative. The canonical equation is solved by symplectic algorithm. The ground state and the equal weight coherent superposition of the ground state and the first excited state have been taken as the initial conditions, respectively, while we calculate the population of bound states, the evolution of average distance and the high-order harmonic generation (HHG). The conversion efficiency of HHG can be enhanced by initial coherent superposition state and moderate laser intensities     

Modular design of icosahedral metal clusters

The concept of crystalline module, that is, an unambiguously isolated, repeated quasi-molecular element, is introduced. This concept is more general than the concept of crystal lattice. The generalized modular approach allows extension of the methods and principles of crystallography to quasi-crystals, clusters, amorphous solids, and periodic biological structures. Principles of construction of aperiodic, nonequilibrium regular modular structures are formulated. Limitations on the size of icosahedral clusters are due to the presence of spherical shells with non-Euclidean tetrahedral tiling in their structure. A parametric relationship between the structures of icosahedral fullerenes and metal clusters of the Chini series was found.     

Global optimization of univariate Lipschitz functions: II. New algorithms and computational comparison

We consider the following global optimization problems for a Lipschitz functionf implicitly defined on an interval [a, b]. Problem P: find a globally-optimal value off and a corresponding point; Problem Q: find a set of disjoint subintervals of [a, b] containing only points with a globally-optimal value and the union of which contains all globally optimal points. A two-phase algorithm is proposed for Problem P. In phase I, this algorithm obtains rapidly a solution which is often globally-optimal. Moreover, a sufficient condition onf for this to be the case is given. In phase II, the algorithm proves the-optimality of the solution obtained in phase I or finds a sequence of points of increasing value containing one with a globally-optimal value. The new algorithm is empirically compared (on twenty problems from the literature) with a best possible algorithm (for which the optimal value is assumed to be known), with a passive algorithm and with the algorithms of Evtushenko, Galperin, Shen and Zhu, Piyavskii, Timonov and Schoen. For small, the new algorithm requires only a few percent more function evaluations than the best possible one. An extended version of Piyavskii's algorithm is proposed for problem Q. A sufficient condition onf is given for the globally optimal points to be in one-to-one correspondance with the obtained intervals. This result is achieved for all twenty test problems.The research of the authors has been supported by AFOSR grants 0271 and 0066 to Rutgers University. Research of the second author has been also supported by NSERC grant GP0036426, FCAR grant 89EQ4144 and partially by AFOSR grant 0066. We thank Nicole Paradis for her help in drawing the figures.     

一种修正的窄缝电磁耦合FDTD算法

电磁脉冲通过窄缝的耦合计算是电磁兼容研究中的一个重要问题,现有算法存在着一些局限或不足.为得到一种能够反映窄缝实际耦合特点的算法,研究了Wang的窄缝算法中的不足,并基于其提出了一种修正的窄缝电磁耦合FDTD算法,即假设窄缝所在网格上的电磁总场在面向入射场源的窄缝一侧是随离窄缝距离增加而增强的,而在背向入射场源的窄缝一侧是随离窄缝距离的增加而减弱的.用该算法对ESD电流注入细导线产生的电磁场与窄缝的耦合进行了计算.计算结果表明了该算法的正确性.     

基于TMS320C5409的语音处理系统

介绍了一个基于DSP(TMS320C5409)的语音采集、编码、回放系统实例,对于DSP与CODEC芯片如何连接和配合工作提出了较为详细的解决方案,并从硬件、软件两个方面做出了说明.     

用遗传算法模拟复杂最优网络的自然涌现过程

为了模拟复杂最优网络从树演化到完备图的整个过程，解决现有邻接节点编码方法只适用于低密度网络，而传统的交叉变异方法又有大量不可行解的问题，提出了基于三角阵的变长基因编码方法和段间交叉、段内变异平衡的交叉变异方法．该编码方法只记录对称邻接矩阵中三角阵的信息，反映了无向网络的所有可能变化，因而编码串长度适中，网络边数不需限制，可以模拟网络从树到完备图的整个演化过程．段间交叉只交换节点一级近邻的连接方式，段内变异平衡对边进行重绕，这既符合遗传算法的要求，又保证了网络的连通性．模拟结果表明，与邻接节点编码和传统交叉变异方法相比，所提方法适用范围更广，收敛速度较快．     

基于遗传算法扶梯驱动机模糊可靠性优化设计

应用啮合理论和模糊可靠性优化理论，以自动扶梯驱动机主传动机构中蜗杆传动的效率及中心距为目标函数，选取必要的设计参数，并使用改进的遗传算法，对驱动机中的蜗杆传动进行模糊可靠性优化设计．结果表明，该算法具有较强的全局收敛性，且收敛速度和稳定性有所提高，与传统设计方法相比，蜗杆减速器的中心距下降了30．4％，蜗杆的相对滑动速度下降了10．12％，综合曲率半径增大了17．34％．     

BP模型在降雨径流预报中的应用研究

简要介绍了人工神经网络用于洪水预报的基本原理,对降雨径流预报的网络模型进行了改进。为了避免陷于局部极小值和缩短学习时间,采用了改进的自适应BP算法进行洪水预报,开发了基于BP模型的洪水预报系统,并经过山西省文峪河水库的实测资料进行了预报,取得了令人满意的精度。