一类含参广义集值拟变分包含组的解的灵敏性分析

本文引入了一类新的含参广义集值拟变分包含组,应用隐预解算子技巧,建立了该类变分包含组与一类不动点问题的等价性,在适当的条件下,分析了含参广义集值拟变分包含组的解的灵敏性,所得结果推广改进了最新文献中的许多结果．     

矩阵的广义特征值及特征向量的神经网络方法

矩阵特征值及特征向量计算在实际问题中有广泛的应用.应用神经网络方法来计算广义特征值及对应的特征向量,给出了相应的算法,并对给出的算法在数学上进行了严格证明.并用实例验证了其正确性.     

用Java实现网上结构图实验仿真

基于线性系统仿真的连接矩阵方法，用Java语言开发面向结构图的实验仿真程序，以Applet小应用程序的形式插入网页中运行，实现了信号与系统网上实验教学中的结构图实验仿真。经试用，程序在浏览器中运行正常，可以完成一般线性系统仿真，与以MATLAB，LABView等程序开发的实验仿真程序相比，该程序运行环境简单，几乎所有常用的Web浏览器都支持Java运行，不需另行安装相应组件。对于线性系统结构图，实现了所见即所得的图形化编程环境，具有较好的人机交互性。     

Coxeter Transformation and Quasiquivers

Mathematical Notes -     

(Anti-)de Sitter Black Hole Entropy and Generalized Uncertainty Principle

We generalize the method that is used to study corrections to Cardy-Verlinde formula due to generalized uncertainty principle and discuss corrections to Cardy-Verlinde formula due to generalized uncertainty principle in (anti)-de Sitter space. Because in de Sitter black hole spacetime the radiation temperature of the black hole horizon is different from the one of the cosmological horizon, this spacetime is a thermodynamical non-equilibrium spacetime.     

Some remarks to multivariate regression model

Some remarks to problems of point and interval estimation, testing and problems of outliers are presented in the case of multivariate regression model. This work was supported by the Council of Czech Government J14/98:153100011.     

Irregularities of distribution with respect to strips

Summary A lower bound is established for the strip discrepancy of a broad class of point distributions. The bound implies unbounded strip discrepancy for equally weighted point distributions under favorable conditions. The methods of proof use notions from integral geometry.     

Heuristic Solution Methods for the Multilevel Generalized Assignment Problem

The multilevel generalized assignment problem is a problem of assigning agents to tasks where the agents can perform tasks at more than one efficiency level. A profit is associated with each assignment and the objective of the problem is profit maximization. Two heuristic solution methods are presented for the problem. The heuristics are developed from solution methods for the generalized assignment problem. One method uses a regret minimization approach whilst the other method uses a repair approach on a relaxation of the problem. The heuristics are able to solve moderately large instances of the problem rapidly and effectively. Procedures for deriving an upper bound on the solution of the problem are also described. On larger and harder instances of the problem one heuristic is particularly effective.