慢时变线性模型参数辨识递推算法及收敛性分析

针对慢时变线性模型,给出辨识的递推算法,并证明该算法能够保证参数收敛在一个有界空间区域,该区域包含参数真值集合;若工作点不发生变化,合理的收敛因子保证参数收敛到对应真值.在实际应用中,工业对象可以利用慢时变线性模型表示,因此该递推算法能够确保工业对象模型实时更新以跟踪工况的变化.通过实例仿真可以看出,该递推算法能够保证慢时变线性模型参数有效更新,并较为准确估计输出变量.     

基于投影寻踪模型的我国国防科技工业科研创新能力实证研究

在有关成果数据库(2000~2006年)的基础上,运用投影寻踪模型分析我国国防科技工业的科研创新能力,结论认为:我国科技工业科研创新能力在最近这几年是逐年提高,进步显著;但与发达国家相比,我国国防科技工业自主创新能力还不够强,距离创新型国防科技工业还有较大的差距。     

高阶复域微分方程解取小函数的收敛指数

研究了亚纯函数系数的高阶复域微分方程的解取小函数的点的收敛指数,得到了方程的解取小函数的点的收敛指数的精确估计.     

二重级数收敛性研究

研究了二重级数和累次级数收敛问题,提出了二重级数与累次级数收敛的判别法并给出了证明,在此基础上研究了二者之间的关系,丰富了级数基本理论.     

S7上保持正曲率的3维塌缩

证明了七维欧氏球面S7上存在一系列正曲率度量,使得在Gromov-Hausdorff收敛的意义下塌陷到S41/2,即常曲率为4的四维单连通空间型.     

一个新的四阶迭代法和一族新的三阶迭代法

目的研究解非线性方程组中的算法问题,得到更高收敛阶的迭代法。方法采用离散C-方法,用数值例子与其他方法进行比较。结果得到一族三阶迭代法且参数取特定值时得到解非线性方程组的一个四阶迭代法。结论此迭代法对解非线性方程组有极其重要的意义。     

一个新的非单调自动确定信赖域半径的信赖域算法

将非单调线搜索技术与自动确定信赖域半径的方法相结合,提出了求解无约束优化问题的一个新的非单调自动确定信赖域半径的信赖域算法.在假设对任意x1∈Rn,水平集L(x1)={x|f(x)≤f(x1)}有界,且目标函数f(x)在水平集L(x1)上连续可微;矩阵序列{Bk}一致有界的条件下证明了本算法的全局收敛性.数值结果显示本算法是有效的.     

A survey of next generation mobile communications research in China

With the rapid development of wireless communication networks, the fourth generation (4G) has emerged to move beyond the limitations of the third generation (3G), with increased bandwidth, enhanced quality of services, and reduced costs of resources. In this paper, we discuss the key technologies of 4G and focus on surveying the ongoing research in 4G communications in China. The 4G technologies under investigation include multicarrier transmission, multiple antenna techniques, carrier aggregation, relays, cognitive radio, distributed antenna systems, network convergence, and network self-optimization. These technologies are the building blocks of 4G and contribute largely to the requirements of International Mobile Telecommunications Advanced (IMT-Advanced). For each technology, its benefits, research topics, and some existing approaches are examined. Finally, we briefly discuss the challenges and future research issues in 4G systems.     

Operational properties and matrix representations of quantum measures

Denoted by M(A), QM(A) and SQM(A) the sets of all measures, quantum measures and subadditive quantum measures on a σ-algebra A, respectively. We observe that these sets are all positive cones in the real vector space F(A) of all real-valued functions on A and prove that M(A) is a face of SQM(A). It is proved that the product of m grade-1 measures is a grade-m measure. By combining a matrix M _μ to a quantum measure μ on the power set A _n of an n-element set X, it is proved that μ ≪ ν (resp. μ ⊥ ν) if and only if M _μ ≪ M _ν (resp. M _μ M _ν =0). Also, it is shown that two nontrivial measures μ and ν are mutually absolutely continuous if and only if μ·ν∈QM(A _n ). Moreover, the matrices corresponding to quantum measures are characterized. Finally, convergence of a sequence of quantum measures on A _n is introduced and discussed; especially, the Vitali-Hahn-Saks theorem for quantum measures is proved.     

模糊数值函数的统计收敛,一致统计收敛及等度统计收敛

 在引入模糊数值函数统计收敛,一致统计收敛,等度统计收敛等概念的基础上,讨论了它们之间的相互关系以及其水平截函数之间的关系.在测度有限的情况下,得到了模糊数值函数统计收敛的Egorov定理和勒贝格定理.