C*-丛中的Morita等价定理

给定C^*-丛(E，P，G)．首先证明了E上循环*表示由Ea决定；然后证明了：C^*(E)与E0强Morita等价．     

辫子群的双参数不可约表示

在广义的Conway条件下,引入双参数完备算符集,借助杨图,给出了B_n群的双参数不可约表示。     

一类m-KP方程的谱表示及其拟周期解

This paper gives the spectral representation of a class of (2 1)-dimensional mod- ified Kadomtsev-Petviashvili(m-KP) equation with a constant parameter.Its quasi-periodic solution is obtained in terms of Riemann theta functions.     

利用双参变形自旋相干态计算量子代数SU(2)q,s的Clebsch-Gordan系数

利用量子代数SU(2)_q,s的双参数变形自旋相干态,通过引入量子代数SU(2)_q,s的不可约表示张量积空间的Bargmann表示,导出了这一表示中不可约表示基底、双参数变形自旋相干态以及算符的表达式.最后导出了量子代数SU(2)_q,s在双参数变形自旋相干态下的Clebsch－Gordan系数.     

车辆路径问题的混合优化算法

讨论了一类车辆路径调度问题(VRP)及其数学模型，并且分析了以遗传算法求解该类问题时的染色体表示和有关遗传操作，然后结合2-opt局部优化算法提出了GA with2-opt算法来求解VRP问题，试验结果说明了该算法的有效性和可行性。     

对称正定问题多搜索方向共轭梯度法的收敛性理论

In this paper, we give the convergence and consistence theory of multiple search direction conjugate gradient method (see [10]) and give some upper bound estimations of iterative value and error of our method.     

标值累计映射

本文证明随机矢量值测度的存在定理以及便于应用的另一形式存在定理，并用它证明将稀疏算子的表达式中的两点分布的概率函数换为非负实值随机过程的概率分布所得的标值累计映射的存在定理。稀疏算子的绝大部分性质被平行推广到标值累计映射。     

单电子能量的解析隐函数表示

本文提出多核体系中单电子能量的解析隐函数表示。此方法建立在直接空间里的原子轨道线性组合和动量空间里波函数的表示。从理论上讲,任何级别的精确值都可以用叠代法求得。文中还讨论了此方法在和键角键长变化有关的分子课题中的可能应用。     

A Frisch-Newton Algorithm for Sparse Quantile Regression

Recent experience has shown that interior-point methods using a log barrier approach are far superior to classical simplex methods for computing solutions to large parametric quantile regression problems. In many large empirical applications, the design matrix has a very sparse structure. A typical example is the classical fixed-effect model for panel data where the parametric dimension of the model can be quite large, but the number of non-zero elements is quite small. Adopting recent developments in sparse linear algebra we introduce a modified version of the Prisch-Newton algorithm for quantile regression described in Portnoy and Koenker~([28]). The new algorithm substantially reduces the storage (memory) requirements and increases computational speed. The modified algorithm also facilitates the development of nonparametric quantile regression methods. The pseudo design matrices employed in nonparametric quantile regression smoothing are inherently sparse in both the fidelity and roughness penalty components. Exploiting the sparse structure of these problems opens up a whole range of new possibilities for multivariate smoothing on large data sets via ANOVA-type decomposition and partial linear models.