一类随机积分-微分方程的均方渐近概周期解

随机微分方程是在解决某些具有随机现象建立起来的一类方程,其中随机微分方程的均方渐近概周期解相比于均方概周期解应用更加广泛.为了研究均方渐近概周期过程在随机微分方程中的应用,利用均方渐近概周期函数的相关性质以及Banach不动点原理讨论了一类随机积分-微分方程均方渐近概周期解的存在性和唯一性.     

曲线箱梁桥的空间传递矩阵

为了分析曲线箱梁桥的受力情况,将传递矩阵法用于曲线箱梁桥的受力分析,以变化固定端的悬臂梁作为单元基本计算体系,利用平衡方程、卡式定理及虚功原理推导了弹性曲线箱梁的显式空间传递矩阵,并考虑了截面剪切中心与形心不重合的影响。为验证公式的正确性,分别采用传递矩阵法与有限元法对某一单跨曲线箱梁桥进行空间受力分析,结果显示2种方法计算结果基本吻合,而传递矩阵法划分较少单元却可达到很高的精度,计算效率大大提高。表明该公式正确,推导方法可行,可推广应用于其他结构在不同荷载情况下传递矩阵的推导。     

拉格朗日中值定理的应用

通过实例,介绍拉格朗日中值定理在求极限、证明不等式、证明恒等式及证明与区间端点函数值有关的等式中的应用.     

AVO流体反演技术在低孔渗砂岩气藏预测中的应用

西湖凹陷A构造的砂岩气藏,主要埋藏于3000m以下的深层,且发育于浅水沉积环境,储层物性较致密,厚度横向变化大,导致储层的AVO响应复杂,常规AVO分析难以对储层流体进行有效识别。研究了AVO流体反演技术在该构造含气储层预测中的应用。该技术在对储层以及非储层速度、密度、厚度等关键参数的统计分析的基础上,利用Monte－Carlo随机模型建立、地震正演模拟、流体替换等技术,获得储层在不同流体下AVO响应的验前概率;然后利用Bayes理论,估算实际地震数据AVO响应指示储层含某种流体的可能性一验后概率,从而实现储层流体的预测。实际钻探结果证实了该方法的有效性。     

Low-temperature phase formation in the SrF2–LaF3 system

Phase formation in the SrF₂–LaF₃ system was studied at temperatures ranging from 300°C to 450°C using nitrate flux. The solubility of LaF₃ in SrF₂ decreases with decreasing temperature. The equilibrium width of the solid solution region Sr_1−xLa_xF_2+x at 400°C, it is 44.6 ± 0.4 mol% LaF₃ (x = 0.446), at 350°C — 38.3 ± 0.7 mol% LaF₃ (x = 0.383), and decreases almost to zero at 300°C.     

随机背包公钥密码的分析与改进

针对随机背包公钥密码方案,提出一种私钥恢复攻击方法.发现Wang等人所构造的随机背包公钥方案实际上是隐含使用了一个特殊的超递增背包.通过使用普通超递增背包代替该特殊超递增背包,将超递增背包隐藏在随机选择的背包中,对原方案进行了改进,提出一种新的基于中国剩余定理的背包公钥密码方案.改进后的方案消除了原方案存在的设计缺陷,能够抵抗针对原方案提出的格规约攻击、低密度攻击以及shamir攻击.     

基于网络编码的无线网络容量分析

无线网络容量一直是无线网络领域的研究热点,而网络编码通过赋予中间节点对接收数据包进行编码、组合的能力,可以有效提高网络容量,达到最大流—最小割定理确定的理论上限.本文在Gupta和Kumar提出的信号干扰噪声比模型基础上,首先分析网络节点均匀分布时发送节点与目的节点进行多跳传输的无线网络容量计算方法;接着推导出了基于网络编码的无线网络容量计算公式,并利用MATLAB中求解线性规划问题的函数linprog()求解网络最大流及各链路流量,以此求出无线网络容量上界.通过对无线网络容量上界进行MATLAB仿真,得到如下结论:无线网络容量上界随节点数量的增加呈现先增加后减少的趋势;且当节点数量趋于无穷大时,网络容量趋于零;与传统的存储转发模式相比,采用网络编码有利于提高网络容量.     

Input‐output triggered control using ‐stability over finite horizons

This paper investigates stability of nonlinear control systems under intermittent information. Following recent results in the literature, we replace the traditional periodic paradigm, where the up‐to‐date information is transmitted and control laws are executed in a periodic fashion, with the event‐triggered paradigm. Building on the small gain theorem, we develop input–output triggered control algorithms yielding stable closed‐loop systems. In other words, based on the currently available (but outdated) measurements of the outputs and external inputs of a plant, a mechanism triggering when to obtain new measurements and update the control inputs is provided. Depending on the noise in the environment, the developed algorithm yields stable, asymptotically stable, and ‐stable (with bias) closed‐loop systems. Control loops are modeled as interconnections of hybrid systems for which novel results on ‐stability are presented. The prediction of a triggering event is achieved by employing ‐gains over a finite horizon. By resorting to convex programming, a method to compute ‐gains over a finite horizon is devised. Finally, our approach is successfully applied to a trajectory tracking problem for unicycles. Copyright © 2014 John Wiley & Sons, Ltd.     

Probability‐weighted nonlinear stochastic optimal control strategy of quasi‐integrable Hamiltonian systems with uncertain parameters

The nonlinear stochastic optimal control problem of quasi‐integrable Hamiltonian systems with uncertain parameters is investigated. The uncertain parameters are described by using a random vector with λ probability density function. First, the partially averaged Itô stochastic differential equations are derived by using the stochastic averaging method for quasi‐integrable Hamiltonian systems. Then, the dynamical programming equation is established based on stochastic dynamical programming principle. By minimizing the dynamical programming equation with respect to control forces, the optimal control forces can be derived, which are functions of the uncertain parameters. The final optimal control forces are then determined by probability‐weighted average of the obtained control forces with the probability density of the uncertain parameters as weighting function. The mean control effectiveness and mean control efficiency are used to evaluate the proposed control strategy. The robustness of the proposed control is measured by using the ratios of the variation coefficients of mean control effectiveness and mean control efficiency to the variation coefficients of uncertain parameters. Finally, two examples are given to illustrate the proposed control strategy and its effectiveness and robustness. Copyright © 2014 John Wiley & Sons, Ltd.     

On the Controllability of Nonlocal Second‐Order Impulsive Neutral Stochastic Integro‐Differential Equations with Infinite Delay

In this paper, we investigate the controllability for a class of nonlocal second‐order impulsive neutral stochastic integro‐differential equations with infinite delay in Hilbert spaces. More precisely, a set of sufficient conditions for the controllability results of nonlocal second‐order impulsive neutral stochastic integro‐differential equations with infinite delay are derived by means of the Banach fixed point theorem combined with theories of a strongly continuous cosine family of bounded linear operators. As an application, an example is provided to illustrate the obtained theory.