资产重组中金融风险的H∞控制理论应用研究

在随机资产模型的基础上，建立了资产重组问题的离散时间系统模型，运用降阶方法推导了在资产重组过程中使风险最小的奇异控制策略．最后，根据复变函数理论求解范数的方法求得了问题的解析解．     

基于FLANN的动态称重法

根据“逆模型”的思想 ,利用神经元网络良好的逼近能力 ,基于函数联接型神经网络 ( FLANN)的传感器动态补偿方法和最小二乘法 ,提出了一种车辆动态称重解决新方法     

The measuring method of early lateral energy fraction in the scale model experiments

This paper introduces a measuring method of early lateral energy fraction in the scale model experiments. According to the interference principle of half wave length making the high frequency figure-8 directional microphone. With the signal-processing technique, a receiving and analyzing system, for the measurements of lateral energy fraction in the scale model is realized.     

食品中大肠菌群实际检测过程中关键问题的探讨

本文通过一些典型试验分析探讨,解决大肠茵群实际操作过程中的关键问题.结果如下:在鉴别培养基上得到大肠菌群典型茵落特征时,可以直接出报告;初发酵以是否产酸作为阳性管判断的依据,准确度会提高;固体样品初发酵稀释度选择方法为:100、10-1、10-2.     

神经元网络——它的背景、进展和问题

近年来神经元网络研究的进展,在国际学术界引起了强烈的轰动,成了各界学人的热门话题.本文分析了神经元网络研究的来龙去脉,简要介绍了若干代表性的进展,指出了这一研究的意义、问题和进一步研究的方向,希望引起各界同仁的关注.     

高压射流的理论分析

本文研究了高压射流装置喷咀部分液流的动态特性,建立了数学模型,讨论了一种拟线性偏微分方程组的哥西问题,并利用特征线将此问题转化为非线性积分方程组,给出了它解的存在唯一条件和解的逐次迭代公式。     

基于蚁群思想的源攻击追踪方法

在现有的攻击源追踪技术中还存在不少弊端,例如:输入测试法需要技术人员的干预,ICMP定位法占用网络带宽资源等,并且事后不能准确地追踪到攻击的源头.提出一种基于蚁群思想的网络协同源攻击追踪方法,通过使用IMCP定位报文法的策略,在网络监测器上对攻击数据包进行“备份”,然后再利用蚁群算法缩小路径信息查询的范围,从而能够快速的构造出攻击路径.实验表明:该方法提高了追踪信息的查询速度和攻击源定位的准确性.     

Simulation of X-ray pulsar signals with multiphysical properties

In view of the few and discontinuous X-ray pulsar data, based on the physical properties of the X-ray pulsar real data from the Rossi X-ray Timing Explorer (RXTE) spacecraft, this paper adopts the fast iterative method and the 10 μs time transformation model, simulates the X-ray pulsar signals which have the periodic property, spectral property, and the background noise property as well as a variety of delay effects. We design and implement simulation software which can simulate the X-ray pulsar signals with multi-physical properties. The results of comparing the real data and simulation data in the same situation show that the simulation noises and the actual noises have the same distribution, that the period stability of the simulated X-ray pulsar data agrees with the real data, with the error of only 0.43％, in different energy levels, that the simulated data's integrated profile and the real data's standard profile are highly correlated with the Pearson correlation coefficient of 0.99, and that under the 10μs time transformation model, the time conversion accuracy of the simulation data can reach 10^-7s, the error between the simulation and the real data being just only 10^-7s, which meets the time transformation accuracy. Therefore, the proposed method can realize the high-fidelity simulations and generate the continuous pulsar signal with many physical properties.     

Gaussian process assisted coevolutionary estimation of distribution algorithm for computationally expensive problems

In order to reduce the computation of complex problems, a new surrogate-assisted estimation of distribution algorithm with Gaussian process was proposed. Coevolution was used in dual populations which evolved in parallel. The search space was projected into multiple subspaces and searched by sub-populations. Also, the whole space was exploited by the other population which exchanges information with the sub-populations. In order to make the evolutionary course efficient, multivariate Gaussian model and Gaussian mixture model were used in both populations separately to estimate the distribution of individuals and reproduce new generations. For the surrogate model, Gaussian process was combined with the algorithm which predicted variance of the predictions. The results on six benchmark functions show that the new algorithm performs better than other surrogate-model based algorithms and the computation complexity is only 10% of the original estimation of distribution algorithm.