长途电话站CSIMAN仿真系统输出结果的置信概率

对长途电话站的ＣＳＩＭＡＮ仿真系统中输出结果置信概率进行了详细的分析。     

Synchronization of neural networks based on parameter identification and via output or state coupling

For neural networks with all the parameters unknown, we focus on the global robust synchronization between two coupled neural networks with time-varying delay that are linearly and unidirectionally coupled. First, we use Lyapunov functionals to establish general theoretical conditions for designing the coupling matrix. Neither symmetry nor negative (positive) definiteness of the coupling matrix are required; under less restrictive conditions, the two coupled chaotic neural networks can achieve global robust synchronization regardless of their initial states. Second, by employing the invariance principle of functional differential equations, a simple, analytical, and rigorous adaptive feedback scheme is proposed for the robust synchronization of almost all kinds of coupled neural networks with time-varying delay based on the parameter identification of uncertain delayed neural networks. Finally, numerical simulations validate the effectiveness and feasibility of the proposed technique.     

On the use of fuzzy inference techniques in assessment models: part I—theoretical properties

An assessment model is a mathematical model that produces a measuring index, either in the form of a numerical score or a category to a situation/object, with respect to the subject of measure. From the numerical score, decision can be made and action can be taken. To allow valid and useful comparisons among various situations/objects according to their associated numerical scores to be made, the monotone output property and the output resolution property are essential in fuzzy inference-based assessment problems. We investigate the conditions for a fuzzy assessment model to fulfill the monotone output property using a derivative approach. A guideline on how the input membership functions should be tuned is also provided. Besides, the output resolution property is defined as the derivative of the output of the assessment model with respect to its input. This derivative should be greater than the minimum resolution required. From the derivative, we suggest improvements to the output resolution property by refining the fuzzy production rules.     

The process of management review

Management review of the quality-management system is an item in many quality standards and a requirement of the ISO 9001:2000 standard and of laboratory standards ISO 15189 and ISO 17125, and others. These reviews are conducted to ensure that the top management is informed and involved in the quality-management system with respect to continuing adequacy and effectiveness, and opportunities for improvement of the system. The management review is a process that should be conducted and audited utilizing the process approach. A process approach is defined as “An activity using resources and managed in order to enable the transformation of inputs into outputs” (ISO 9001:2000). All identified main processes in the quality system should be monitored through data collection by appropriate methods, assuring that data are valid, representative, and adequate. For management review data must be collected and presented in an accessible form so that processes can be evaluated according to objectives, goals, resources, etc. On the basis of this information the laboratory management makes the necessary decisions and ensure that actions are taken that improve the effectiveness of the quality-management system. As output from the management review process, there should be evidence of decisions regarding: change of quality policy and objectives; plans and possible actions for improvements; corrective actions as appropriate; increased customer satisfaction; and planning of resources needs. Identification of the processes involved and using the process approach in the management review ensures the continual improvement of the quality system. Presented at the conference Quality in the Spotlight, March 2006, Antwerp, Belgium.     

Polynomial cases of the economic lot sizing problem with cost discounts

In this paper we study the economic lot sizing problem with cost discounts. In the economic lot sizing problem a facility faces known demands over a discrete finite horizon. At each period, the ordering cost function and the holding cost function are given and they can be different from period to period. There are no constraints on the quantity ordered in each period and backlogging is not allowed. The objective is to decide when and how much to order so as to minimize the total ordering and holding costs over the finite horizon without any shortages. We study two different cost discount functions. The modified all-unit discount cost function alternates increasing and flat sections, starting with a flat section that indicates a minimum charge for small quantities. While in general the economic lot sizing problem with modified all-unit discount cost function is known to be NP-hard, we assume that the cost functions do not vary from period to period and identify a polynomial case. Then we study the incremental discount cost function which is an increasing piecewise linear function with no flat sections. The efficiency of the solution algorithms follows from properties of the optimal solution. We computationally test the polynomial algorithms against the use of CPLEX.     

用VxD实现并行数据通讯

通过开发实例介绍了在Delphi5 .0中利用虚拟设备驱动程序进行动态加载 ,实现与并行采集卡通讯的技术方法 .     

线性系统的输出反馈特征结构配置——具有不可控不可观模态的情形

本文考虑具有不可控不可观模态的线性系统的输出反馈特征结构配置问题。根据文中给出的矩阵方程AV＋BW＝VF的一种显式参数解，得到了线性系统的输出反馈特征结构配置的一种参数化方法，本文没有对系统附加能控能观条件，在[AB]能控的条件下，本文得到的矩阵方程的解是文[5]中定理2的结果，在[AB]能控且[AC]能观的条件下，本文得到的输出反馈特征结构配置方法是文[6]在系统为定常时算法Ⅱ的结果。     

Incremental unknowns in three-dimensional stationary problem

The main purpose of this work is to set up the explicit matrix framework appropriate to three-dimensional partial differential equations by means of the incremental unknowns method. Multilevel schemes of the incremental unknowns are presented in the three space dimensions, and through numerical experiments, we confirm that the incremental unknowns method is efficient and the hierarchical preconditioning based on the incremental unknowns can be applied in a more general form.      

Robust output feedback stabilization for two-dimensional continuous systems in roesser form

This paper considers the problem of robust stabilization via dynamic output feedbackcontrollers for uncertain two-dimensional continuous systems described by the Roesser's state space model. The parameter uncertainties are assumed to be norm-bounded appearing in all the matrices of the system model. A sufficient condition for the existence of dynamic output feedback controllers guaranteeing the asymptotic stability of the closed-loop system for all admissible uncertainties is proposed. A desired dynamic output feedback controller can be constructed by solving a set of linear matrix inequalities. Finally, an illustrative example is provided to demonstrate the applicability and effectiveness of the proposed method.