广义生-灭最小Q过程的常返、遍历性

研究具有突变率的全稳定广义生-灭最小Q过程的常返性和遍历性,在Q-矩阵是正则、不可约的条件下,利用Q过程的构造理论,获得广义生-灭最小Q过程是常返、遍历的易于检验的充分必要条件,并给出不变测度.     

生灭矩阵重构三弦乐谱

三弦乐谱可由三对角复矩阵生成,人们听到的声音由其谱决定,自然要求此矩阵有实谱.如同量子力学,模型的描述是复算子,可观测量是实的.换言之,所述的三对角复矩阵应是关于某个测度的复内积空间上的自共轭算子.熟知,生灭Q矩阵可配称,自然就是自共轭的.我们将要介绍最新的一个代表性成果:对于相当广泛的自共轭三对角复矩阵,总可以构造出一个生灭Q矩阵,使得两者等谱(简单地说,两者有完全相同的特征值).这个问题浅显易懂,但我们曾在不同时期,从概率论、统计物理和计算数学三个不同的角度研究过,经历了漫长的求索岁月.本文是根据作者在"International Conference on Probability Theory and Its Applications"(湖南文理学院,2018年7月)的报告整理而成.共分三部分:1)生灭过程的新应用;2)从(非对角线元素非负的)实可配称矩阵到复可配称矩阵;3)此课题的来源(计算)及其判别准则的应用(统计物理及量子力学).     

含瞬时态、具有突变率的广义生-灭Q-矩阵(I)

研究含瞬时态、具有突变率的广义生-灭拟q-矩阵,给出易于验证的Q过程存在性准则,并构造出全部Q过程和全部诚实Q过程,证明了不需附加任何条件,所有诚实Q过程都是常返的,给出诚实Q过程是遍历的充要条件,并求出其遍历测度,以及证明了不存在可配称Q过程.最后给出两个例子以说明我们的结果易于验证.     

含瞬时态、具有突变率的广义生-灭Q-矩阵(Ⅰ)

研究含瞬时态、具有突变率的广义生-灭拟q-矩阵,给出易于验证的Q过程存在性准则,并构造出全部Q过程和全部诚实Q过程,证明了不需附加任何条件,所有诚实Q过程都是常返的,给出诚实Q过程是遍历的充要条件,并求出其遍历测度,以及证明了不存在可配称Q过程.最后给出两个例子以说明我们的结果易于验证.     

含瞬时态、具有突变率的广义生-灭Q-矩阵(Ⅱ)

研究含瞬时态、具有突变率的广义生-灭拟q-矩阵,在QE0o非零流出下,给出易于验证的Q过程存在性准则,并构造出全部Q过程和全部诚实Q过程,证明了不需附加任何条件,所有诚实Q过程都是遍历的,并求出其遍历测度以及给出诚实Q过程可配称的充要条件.最后给出两个例子以说明本文的结果易于验证.     

含瞬时态、具有突变率的广义生-灭Q-矩阵(Ⅱ)

研究含瞬时态、具有突变率的广义生-灭拟q-矩阵,在Q_(E_0)非零流出下,给出易于验证的Q过程存在性准则,并构造出全部Q过程和全部诚实Q过程,证明了不需附加任何条件,所有诚实Q过程都是遍历的,并求出其遍历测度以及给出诚实Q过程可配称的充要条件。最后给出两个例子以说明本文的结果易于验证。     

单瞬时态可逆Q过程存在性问题

本文给出了单瞬时准保守可逆 Q 过程和不中断可配称 Q 过程的存在准则.     

生灭Q－矩阵

对于一般（不必全稳定）单边、双边拟生灭矩阵，本文分别给出了它们成为Ｑ－矩阵和诚实Ｑ－矩阵的充分必要条件；而且还分别得到了Ｑ过程和诚实Ｑ过程的唯一性准则．即，彻底解决了一般单边、双边生灭过程和诚实生灭过程的存在唯一性问题。     

生灭Q－矩阵

对于一般（不必全稳定）单边、双边拟生灭矩阵，本文分别给出了它们成为Ｑ－矩阵和诚实Ｑ－矩阵的充分必要条件；而且还分别得到了Ｑ过程和诚实Ｑ过程的唯一性准则．即，彻底解决了一般单边、双边生灭过程和诚实生灭过程的存在唯一性问题。     

具有突变率的广义生-灭过程——随机单调性、Feller性及可配称性

本文给出了具有突变率的广义生－灭过程的随机单调性、Feller性及可配称性的充要条件。     

两类带有确定潜伏期的SEIS传染病模型的分析

通过研究两类带有确定潜伏期的SEIS传染病模型,发现对种群的常数输入和指数输入会使疾病的传播过程产生本质的差异．对于带有常数输入的情形,找到了地方病平衡点存在及局部渐近稳定的阈值,证明了地方病平衡点存在时一定局部渐近稳定,并且疾病一致持续存在．对于带有指数输入的情形,发现地方病平衡点当潜伏期充分小时是局部渐近稳定的,当潜伏期充分大时是不稳定的．     

Polynomial-time algorithms for regular set-covering and threshold synthesis

A set-covering problem is called regular if a cover always remains a cover when any column in it is replaced by an earlier column. From the input of the problem - the coefficient matrix of the set-covering inequalities - it is possible to check in polynomial time whether the problem is regular or can be made regular by permuting the columns. If it is, then all the minimal covers are generated in polynomial time, and one of them is an optimal solution. The algorithm also yields an explicit bound for the number of minimal covers. These results can be used to check in polynomial time whether a given set-covering problem is equivalent to some knapsack problem without additional variables, or equivalently to recognize positive threshold functions in polynomial time. However, the problem of recognizing when an arbitrary Boolean function is threshold is NP-complete. It is also shown that the list of maximal non-covers is essentially the most compact input possible, even if it is known in advance that the problem is regular.     

一类具有垂直传染和预防接种的SEIR传染病模型的定性分析

建立并分析了一类对出生时没有被染病母体垂直传染的染病者的新生儿进行免疫接种的SEIR传染病模型.得到了疾病是否灭绝的阈值R0,当R0<1时,无病平衡点全局渐近稳定的.当R0>1时,地方病平衡点局部渐近稳定的,且疾病一致持续生存.     

Milnor方图中的w-凝聚性

整环R称为ω-凝聚整环,是指R的每个有限型理想是有限表现型的.本文证明了ω-凝聚整环是v-凝聚整环,且若(RDTF,M)是Milnor方图,则在Ⅰ型情形,R是ω-凝聚整环当且仅当D和T都是ω-整环,且T_M是赋值环;对于Ⅱ-型情形,R是ω-凝聚整环当且仅当D是域,[F:D]<∞,M是R的有限型理想,T是ω-凝聚整环,且R_M是凝聚整环.     

带有反馈的因果模型中的独立性识别

在本文中,直接利用计算要概率分布的办法证明了在史包含离散变量４ 反馈系统产生的因果图中的条件独立关系可以由ｄ－分离识别出．     

On the density of the minimal subspaces generated by discrete linear Hamiltonian systems

This paper focuses on the density of the minimal subspaces generated by a class of discrete linear Hamiltonian systems. It is shown that the minimal subspace is densely defined if and only if the maximal subspace is an operator; that is, it is single valued. In addition, it is shown that, if the interval on which the systems are defined is bounded from below or above, then the minimal subspace is non-densely defined in any non-trivial case.     

The Cauchy problem for a generalized Camassa–Holm equation

In this paper, we are concerned with the Cauchy problem of the generalized Camassa–Holm equation. Using a Galerkin-type approximation scheme, it is shown that this equation is well-posed in Sobolev spaces $H^s$, $s>3/2$ for both the periodic and the nonperiodic case in the sense of Hadamard. That is, the data-to-solution map is continuous. Furthermore, it is proved that this dependence is sharp by showing that the solution map is not uniformly continuous. The nonuniform dependence is proved using the method of approximate solutions and well-posedness estimates. Moreover, it is shown that the solution map for the generalized Camassa–Holm equation is Hölder continuous in $H^r$-topology. Finally, with analytic initial data, we show that its solutions are analytic in both variables, globally in space and locally in time.     

递推阻尼最小二乘法的收敛性与稳定性

递推最小二乘法是参数辨识中最常用的方法,但容易产生参数爆发现象.因此对一种更稳定的辨识方法——递推阻尼最小二乘法进行了收敛特性的分析.在使用算法之前先归一化测量向量,结果表明,参数化距离收敛于一个零均值随机变量,并且在持续激励条件下,适应增益矩阵的条件数有界.参数化距离的方差有界.     

An Improved Branch & Bound Method for the Uncapacitated Competitive Location Problem

In this paper, the problem of locating new facilities in a competitive environment is considered. The problem is formulated as the firm expected profit maximization and a set of nodes is selected in a graph representing the geographical zone. Profit depends on fixed and deterministic location costs and, since customers are independent decision-makers, on the expected market share. The problem is an instance of nonlinear integer programming, because the objective function is concave and submodular. Due to this complexity a branch & bound method is developed for solving small size problems (that is, when the number of nodes is less than 50), while a heuristic is necessary for larger problems. The branch & bound is called data-correcting method, while the approximate solutions are obtained using the heuristic-concentration method.     

AR（p）模型中的缺失数据估计

运用EM算法,对含有缺失数据的AR（p）模型进行参数估计,通过最大似然准则就非左端缺失的情况进行插补.最后,用蒙特卡洛方法给出实验分析,表明如下结果：（i）误差与AR模型的阶数正相关,与缺失比例正相关;（ii）当AR模型的特征根模长相对较小时,误差与数据长度负相关,且误差被控制在了标准差的30％以内;（iii）当模长中等时,误差基本控制在1个标准差左右;（iv）当模长较大时,误差与数据长度正相关,而且误差也相对较大.