Adaline对权扰动敏感性的近似计算

主要讨论Adaline对权扰动敏感性的计算.鉴于Adaline的输入和输出的不连续性,敏感性定义为Adaline对于所有可能输入在权值发生扰动的情况下输出发生变化的概率.借助超球面模型和解析几何的技术,给出一个近似计算Adaline敏感性的方法.在输入维数足够大的情况下,该方法优于以往的其它方法.它在牺牲少量计算精度的情况下,极大地降低了计算复杂度,使得敏感性更具实用价值.     

具有大时延的网络控制系统的稳定性分析

针对一类具有随机大时延(大于一个采样周期)的网络控制系统，通过对系统的离散化，从理论上分析了系统的稳定性．利用分割的思想处理随机的网络时延，采用高线控制器设计与在线切换规律设计相结合的方法，给出了系统基于控制器切换技术的稳定的梯度算法．仿真算例说明了结论与算法的正确性．     

基于开环2闭环控制的离散动力系统同步研究

基于开环-闭环控制,提出了一种离散动力系统同步方法.系统地论述了该方法的基本原理,指出了该方法在实际应用中应注意的一系列问题.在此基础上,推导出为实现系统同步应采取控制策略的具体形式,并从理论上对其鲁棒性进行了论证.数字模拟结果表明,该方法不仅具有较高的同步效率,而且具有很强的适用性,能够在不同条件下实现两个同类或异类离散动力系统的同步.     

基于离散分数阶Fourier变换本征矢量分解的图像加密算法

针对目前采用分数阶傅里叶变换对图像进行加密的算法中,其主要存在密钥敏感性较差等不足,提出一种将离散分数阶Fourier变换与指数随机相位掩膜、Logistic混沌映射结合起来进行加密的新算法。该算法在加密过程采用离散分数阶Fourier变换本征矢量分解的方法进行运算,显著提高了加密系统的安全性能。首先,对原始图像进行Logistic映射混沌置乱处理,接着与第一个指数随机矩阵A相乘,之后再经α阶离散的分数阶Fourier变换;其次,与第二个指数随机矩阵B相乘,再经β阶离散的分数阶Fourier变换;最后,利用Logistic映射对图像再次进行置乱处理来获得最终的密文图像。仿真结果表明:与其他类似加密机制相比,该加密系统兼顾了更强的密钥敏感性以及更高的安全性。     

基于WNN的两种优化结果在预测控制中的应用*

从优化小波神经网络的角度出发,对两种优化模型从理论上进行建模与推导;根椐预测控制的特点,提出离散小波神经网络模型GA分层优化方法及广义小波神经网络模型优化方法与预测控制相结合的新的应用途径.仿真结果证明了该方法的有效性和可行性,能使实际工程中的预测控制结果得到优化.     

基于粗糙集的两种离散化算法的研究

随着知识发现和数据挖掘的迅速发展,出现了很多的方法,这些方法很多都依赖于离散的数据。但是,大部分现实中应用的数据都带有连续变量的属性。为了使得数据挖掘的技术能够用在这些数据上面,必须进行离散化。文章探讨了基于粗糙集的离散化方法。论文做实验来比较局部和全局离散化算法,实验结果表明,这两种算法对于数据集有敏感性。     

PWM型DC/DC变换器中混沌控制的仿真研究

该文研究如何利用OGY混沌控制技术来消除DC/DC变换器的混沌状态.首先利用数据采样方法得到系统的离散模型,利用计算机技术由该离散模型进行可以得到系统的分叉图,从分叉图中可以看到DC/DC变换器发生了混沌、分叉等非线性现象,然后从理论上说明了如何利用OGY混沌控制策略把工作在混沌状态的DC/DC变换器控制到周期状态,最后利用计算机对DC/DC变换器进行仿真研究,仿真结果证明了该文中基于OGY方法DC/DC变换器混沌控制策略的有效性.     

自主飞艇俯仰角姿态动力学建模及控制

针对平流层信息平台-自主飞艇动力学特性与升降舵操纵角之间的非线性关系,建立飞艇俯仰角姿态动力学模型,将离散滑模变结构控制方法应用于飞艇的俯仰角姿态控制,从理论上证明所提控制方法对控制系统的渐近稳定性,而且有效削弱了跟踪误差轨迹在滑动过程中的抖动现象,增强了控制系统的鲁棒性,计算机仿真实验不仅表明所建立的飞艇俯仰角姿态动力学模型是正确的,离散滑模变结构控制方法适于飞艇的俯仰角姿态跟踪误差的控制,而且验证了对本文提出的控制方法的理论分析.     

一种利用相角对加性隐写模型进行分析的方法

基于图像在加性隐写模型下隐写前后差分直方图离散傅里叶变换与隐写信息离散傅里叶变换间的对应关系, 从隐写前后差分直方图离散傅里叶变换相角的变化入手, 提取特征, 在理论上加以论证并从实验上得到验证。对UCID V2标准图库进行实验, 结果表明, 本方法对加性隐写模型具有很好的检测效果。     

基于复合离散混沌动力系统的序列密码算法

利用复合离散混沌系统的特性,提出了两个基于复合离散混沌系统的序列密码算法.算法的加密和解密过程都是同一个复合离散混沌系统的迭代过程,取迭代的初始状态作为密钥,以明文序列作为复合系统的复合序列,它决定了迭代过程中迭代函数的选择(或明文与密钥),然后将迭代轨迹粗粒化后作为密文.由于迭代对初始条件的敏感性和迭代函数选择的随机性,密钥、明文与密文之间形成了复杂而敏感的非线性关系,而且密文和明文的相关度也很小,从而可以有效地防止密文对密钥和明文信息的泄露.复合离散混沌系统均匀的不变分布还使密文具有很好的随机特性.经分析表明,系统具有很高的安全性.     

A method for discrete stochastic MADM problems based on the ideal and nadir solutions

Many real life decision making problems can be modeled as discrete stochastic multi-attribute decision making (MADM) problems. A novel method for discrete stochastic MADM problems is developed based on the ideal and nadir solutions as in the classical TOPSIS method. In a stochastic MADM problem, the evaluations of the alternatives with respect to the different attributes are represented by discrete stochastic variables. According to stochastic dominance rules, the probability distributions of the ideal and nadir variates, both are discrete stochastic variables, are defined and determined for a set of discrete stochastic variables. A metric is proposed to measure the distance between two discrete stochastic variables. The ideal solution is a vector of ideal variates and the nadir solution is a vector of nadir variates for the multiple attributes. As in the classical TOPSIS method, the relative closeness of an alternative is determined by its distances from the ideal and nadir solutions. The rankings of the alternatives are determined using the relative closeness. Examples are presented to illustrate the effectiveness of the proposed method. Through the examples, several significant advantages of the proposed method over some existing methods are discussed.     

A method based on stochastic dominance degrees for stochastic multiple criteria decision making

In this paper, a novel method based on the stochastic dominance degree (SDD) is proposed to solve a discrete stochastic multiple criteria decision-making (MCDM) problem. Firstly, a concept of stochastic dominance degree is introduced to describe the degree that one alternative dominates another when the SD relation for each pair of alternatives is determined, and a computation formula of the SDD is given. Then, by calculating SDDs, the SDD matrix on pairwise comparisons of alternatives with respect to each criterion is built. Furthermore, the SDD matrices with respect to all the criteria are aggregated into an overall SDD matrix using the simple additive weighting method. Based on the overall SDD matrix, an approach based on the idea of the PROMETHEE-II is developed to obtain the ranking result of alternatives. Finally, two numerical examples are used to illustrate the applicability and effectiveness of the proposed method.     

Piecewise constant timed continuous PNs for the steady state estimation of stochastic PNs

Reliability analysis is often based on stochastic discrete event models like Markov models or stochastic Petri nets. For complex dynamical systems with numerous components, analytical expressions of the steady state are tedious to work out because of the combinatory explosion with discrete models. The computation of numerical approximations is also time consuming due to the slow convergence of stochastic simulations. For these reasons, fluidification can be investigated to estimate the asymptotic behaviour of stochastic processes. The contributions of this paper are to point out that timed continuous Petri nets may lead to biased estimators of the stochastic steady state and to introduce fluid Petri nets with piecewise-constant maximal firing speeds and sufficient conditions in order to obtain unbiased estimators.     

基于自动机的概率计算树逻辑验证方法

根据带有随机特征的复杂信息系统性质验证的需求,针对离散概率回报模型的分层直到公式,提出一种性质验证分析方法。在综合各种离散随机逻辑的基础上,使用一种同时具有迁移回报及迁移步区间表达能力的概率计算树逻辑表示系统模型的分层直到路径公式性质,使用自动机技术建模路径公式,通过构造积模型完成模型与自动机的同步演化,基于积模型给出相应的状态概率满足算法。实例结果验证了该方法的可行性和有效性。     

Experiments on the evaluation of functional ranges using a random interval arithmetic

A software tool using standard and special interval arithmetic operations together with an idea which is developed in the discrete stochastic arithmetic (DSA) approach for round-off error evaluation is proposed in this paper for a statistical computation of functional ranges. The CESTAC method is a Monte Carlo method which uses DSA and provides the accuracy on any computed result with a high probability. On the other hand, interval computation gives a guaranteed interval containing the result but this interval may be in some cases useless because much too wide. Here it is proposed to combine both approaches to obtain a smaller but only highly probable interval containing the range of a rational function for given interval data. Various numerical experiments are given.     

基于超盒的装备系统灵敏度离散化分析

灵敏度分析是装备系统研究和开发过程中的重要环节,装备指标参数的灵敏度分析关系着装备系统研发的成败,但是在以往的灵敏度分析中,并没有针对超盒展开分析.对灵敏度分析方法进行了研究和分析.通过对灵敏度分析流程、作用和意义的介绍.在超盒理论的基础上,分析了连续性灵敏度分析算法,并进行了离散化分析,通过对计算量的试验仿真,将离散化分析和连续性分析的计算量进行对比,指出了离散化分析对于大型复杂系统存在计算量激增的风险.     

一类线性离散时间结构随机跳变系统的逼近滤波算法

提出了具有条件马尔可夫跳变结构的离散时间随机系统的条件滤波方法, 应用随机变结构系统的性质对滤波算法进行简化处理, 并将后验概率密度函数用条件高斯函数来逼近, 得到具有条件马尔可夫结构离散随机系统的逼近最优滤波算法, 最后给出滤波算法的计算步骤并仿真验证了算法的正确性.     

Confidence tori in the analysis of stochastic 3D-cycles

We present a new computer approach to the spatial analysis of stochastically forced 3D-cycles in nonlinear dynamic systems. This approach is based on a stochastic sensitivity analysis and uses the construction of confidence tori. A confidence torus as a simple 3D-model of the stochastic cycle adequately describes its main probabilistic features. We suggest an effective algorithm for construction of the confidence tori using a discrete set of confidence ellipses. The ability of these tori to visualize thin effects observed for the period-doubling bifurcations zone in the stochastic Roessler model are shown. For this zone, the geometrical growth of stochastic sensitivity of the forced cycles under transition to chaos is presented.     

一类双线性随机系统M量测不定LQ控制

研究了带有乘性噪声和受扰动观测的离散时间随机系统不定线性二次(Linear quadratic, LQ) 最优输出反馈控制问题. 对此类问题而言,二次成本函数的加权矩阵不定号,并且最优控制具有对偶效果.为在最优性和计算复杂度间 进行折衷,本文采用了一种M量测反馈控制设计方法.基于动态规划方法,将未来的测量结合到当前控制 计算当中的M量测反馈控制可以通过倒向求解一类与原系统维数相同的广义差分Riccati方程(Generalized difference Riccati equation, GDRE)得到.仿真结果 表明本文提出的算法与目前普遍采用的确定等价性方法相比具有优越性.     

Trajectory sensitivity analysis using discrete Legendre orthogonal polynomials

A method of finite series expansion using discrete Legendre orthogonal polynomials (DLOPs) is applied to the problem of state trajectory sensitivity analysis. The method presented has a distinct advantage in that it reduces the problem of determining the trajectory sensitivity function to that of solving a set of algebraic equations. In addition, the method is simple and amenable to computer computation.