用于研究专家系统的另一神模型──判别树及其寄生树

本文提出的判别树是一种既系统又直观地描述判别思路的模型,寄生树是一种用来判定判别树中结点的子特征的判别树。在专家系统的研究中,应用本模型有三个优点：①可有条理地描述、整理复杂的分类判别知识;②易于转换出相应的产生式规则或框架形式的知识库;③能清晰直观地指导设计高效的判别推理机。     

一种改进的预补偿反向训练0/1式跳空技术方法

预补偿反向训练的0/1式多天线跳空技术,能从物理层上使无线通信更安全。为了进一步改善目标用户的系统复杂度和训练效率,提出了一种改进的预补偿反向训练方法。发射方通过反向训练获得信道特性参数,利用该参数设计补偿系数,并使用该系数对发送信号进行预补偿。目标用户不需要发射方反馈信道信息,也无需调整接收权值。仿真结果表明,在不降低安全性和误比特率的情况下,该方法能够降低目标用户的系统复杂度,提高了训练效率。     

改进人工蜂群算法及其在应急调度优化问题中的应用

针对于大规模灾难发生时首批“生命”物资的应急调度建模及优化求解问题,将受灾点缺失损失评价函数由线性扩充到非线性,对一次性消耗类和连续性消耗类物资建立了多对多约束多目标调度模型。基于Pareto支配和拥挤距离的概念将人工蜂群基本算法应用到此问题的求解,并对算法进行了以下改进：基于反向食物源的定义提出融合反向学习的食物源初始化,以提高初始解的质量;将反向学习策略和广泛学习策略融合到蜜蜂搜索过程,以反向食物源和其他较好食物源信息来引导蜜蜂搜索方向。三种规模的仿真实验表明,所提出算法所求出的非支配前沿解集更具多样性,分布更加广泛和均匀,能够为应急物资调度决策进行支持。     

Recursive Stochastic H2/H∞ Control Problem for Delay Systems Involving Continuous and Impulse Controls

In this paper, we discuss the recursive stochastic H₂/H_∞ control problem of delay systems with random coefficients involving both continuous and impulse controls. By virtue of a new type of forward backward stochastic differential equations, a necessary and sufficient condition for the existence of a unique solution to the control problem under consideration is derived. The existence and uniqueness of the forward backward stochastic differential equations are also be proved.     

Existence of optimal controls for systems driven by FBSDEs

We prove the existence of optimal relaxed controls as well as strict optimal controls for systems governed by non linear forward-backward stochastic differential equations (FBSDEs). Our approach is based on weak convergence techniques for the associated FBSDEs in the Jakubowski S-topology and a suitable Skorokhod representation theorem.     

固定区间Kalman平滑新算法

用现代时间序列分析方法,基于ＡＲＭＡ新息模型和白噪声估值器,提出了一种正向固定区间稳态Ｋａｌｍａｎ平滑新算法和两种反向固定区间稳态Ｋａｌｍａｎ平滑新算法,并给出了保证算法最优性的最优初值公式。算法简单,便于实时应用。仿真例子说明了它们的有效性。     

游泳池池水消毒药剂的探讨

综评了消毒游泳池池水的各种消毒剂,结合我国国情和实际工作提出消毒效果好,经济、简单易行的液氯消毒法。     

Delay-dependent exponential stability of the backward Euler method for nonlinear stochastic delay differential equations

Recently, several scholars discussed the question of under what conditions numerical solutions can reproduce exponential stability of exact solutions to stochastic delay differential equations, and some delay-independent stability criteria were obtained. This paper is concerned with delay-dependent stability of numerical solutions. Under a delay-dependent condition for the stability of the exact solution, it is proved that the backward Euler method is mean-square exponentially stable for all positive stepsizes. Numerical experiments are given to confirm the theoretical results.     

The improved split-step backward Euler method for stochastic differential delay equations

A new, improved split-step backward Euler method is introduced and analysed for stochastic differential delay equations (SDDEs) with generic variable delay. The method is proved to be convergent in the mean-square sense under conditions (Assumption 3.1) that the diffusion coefficient g(x, y) is globally Lipschitz in both x and y, but the drift coefficient f(x, y) satisfies the one-sided Lipschitz condition in x and globally Lipschitz in y. Further, the exponential mean-square stability of the proposed method is investigated for SDDEs that have a negative one-sided Lipschitz constant. Our results show that the method has the unconditional stability property, in the sense, that it can well reproduce stability of the underlying system, without any restrictions on stepsize h. Numerical experiments and comparisons with existing methods for SDDEs illustrate the computational efficiency of our method.