嵌入曲面的特殊图的边染色

设图\,$G$\,是嵌入到欧拉示性数\,$\chi(\Sigma)\geq 0$\,的曲面\,$\Sigma$\,上的图, $\chi'(G)$\,和\,$\Delta(G)$\,分别表示图\,$G$\,的边色数和最大度. 如果\,$\Delta(G)\geq 4$\,且\,$G$\,满足以下条件: (1)\,图$G$中的任意两个三角形$T_1$, $T_2$的距离至少是$2$; (2)\,图\,$G$\,中\,$i$-圈和\,$j$-圈的距离至少是\,$1$, $i,j\in\{3,4\}$; (3)\,图\,$G$\,中没有\,$5$-圈, 则有\,$\Delta(G)=\chi'(G)$.     

单圈图H(p,tK_{1,m})的Laplacian谱刻画

设图\,$H(p,tK_{1,m})$\,是一个顶点数为\,$p+mt$\,的连通单圈图,它是由圈\,$C_{p}$\,的依次相邻的\,$t(1\leq t\leq p)$\,个顶点、每一个顶点分别与星\,$K_{1,m}$\,的中心重合而得到的单圈图. 证明了单圈图\,$ H( p,p K_{1,4})$, $H(p,p K_{1,3})$, $H(p,(p-1)K_{1,3})$\,是由它们的\,Laplacian\,谱确定的,并证明了当\,$p$\,为偶数时,单圈图\,$H(p,$2K_{1,3})$, $H( p,(p-2) K_{1,3})$, $H(p,(p-3)K_{1,3})$\,也是由它们的\,Laplacian\,谱确定的.     

关于Fatou域的结构

给定有理函数$f$的一个不变的多连通吸性域$U$,我们证明存在一个有理函数$g$和它的一个完全不变的Fatou域$V$,使得$(f,U)$和$(g,V)$是全纯共轭的,而且$g$的Julia集的每个非平凡分支都是拟圆周,其内部是一个最多包含一个后临界轨道点的最终超吸性域. 进一步,$g$在相差一个全纯共轭的意义下是唯一的.     

有结构变化的半参数回归模型

结合半参数回归模型和含未知变点的结构变化模型提出 一个新的模型\,---\,有结构变化的半参数回归模型, 给出了新模型的有关参数$\beta,\beta^\ast,\gamma,k$的加权最小二乘估计和$f(t)$的核估计, 证明了参数\, $\beta,\beta^\ast,\gamma$的估计的$\sqrt{n}$\,-相合性, 强相合性, 讨论了模型的检验等问题, 并进一步通过随机模拟验证了新模型的优越性.     

强拟\alpha-预不变凸函数

研究了一类重要的广凸函数------强拟$\alpha$-预不变凸函数,讨论了它与拟\,$\alpha$-预不变凸函数、严格拟\,$\alpha$-预不变凸函数及半严格拟\,$\alpha$-预不变凸函数之间的关系,并在中间点的强拟\,$\alpha$-预不变凸性下得到了它的三个重要的性质定理,同时给出了强拟\,$\alpha$-预不变凸函 数在数学规划中的两个重要应用,这些结果在一定程度上完善了对强拟\,$\alpha$-预不变凸函数的研究.     

基于$\alpha$\,-混合序列的学习机器一致收敛速率的界

Vapnik, Cucker和Smale已经证明了, 当样本的数目趋于无限时, 基于独立同分布序列学习机器的经验 风险会一致收敛到它的期望风险\bd 本文把这些基于独立同分布序列的结果推广到了$\alpha$\,-混合序列, 应用Markov不等式得到了基于$\alpha$\,-混合序列的学习机器一致收敛速率的界     

图的上可嵌入性与围长及相邻顶点度和

$G$是一个阶为$n$围长为$g$的简单图, $u$和$v$是$G$中任意两个相邻顶点, 如果$d_{G}(u)$ + $d_{G}(v)$ $\geq$ $n - 2g + 5$, 则$G$是上可嵌入的; 如果$G$是2-\!边连通(或3-\!边连通)图, 则当 $d_{G}(u)$ + $d_{G}(v)$ $\geq$ $n - 2g + 3$ (或 $d_{G}(u)$ + $d_{G}(v)$ $\geq$ $n - 2g - 5$)时$G$是上可嵌入的, 并且上面3个下界都是紧的.     

一般$\delta$\,-冲击模型中无失效数据的Bayes统计推断

在这篇文章中, 我们针对一般冲击模型, 研究Bayes方法处理无失效数据的问题. 所谓一般$\delta$\,-冲击模型是指系统受到强度为$\lambda$的Poisson冲击, 当两个连续冲击之间时间间隔的长度不属于某个固定的区间[$\delta_1,\delta_2$]时, 系统将失效. 我们分别选择均匀分布和Beta分布作为先验分布, 用Bayes方法和多层Bayes方法得到了参数$\delta_1$和$\delta_2$的估计.     

有界超格上的微分

在有界超格上引入微分,研究了有界超格上微分的一些性质.定义并研究了微分超格的微分超理想和微分超同余,并证明了如果$(L,d)$是一个有界强单微分超格并且$R$是$(L,d)$的一个强微分同余,则$(L/R,g)$仍是一个强单微分超格,其中$g$是由$d$诱导的商超格上的单强微分.     

有限秩的幂零群的自同构(I)

研究了有限秩的幂零群的自同构, 证明了 \qquad {\heiti定理}\quad设幂零群~$G=KP$, 其中~$P$是有限秩的幂零~$p$-\!群, ~$K$ 是~$G$\,的有限秩的~$p^\prime$-\!自由的正规子群, ~$p$\, 不属于~$K$\,的谱~$S_p(K)$. 设~$\alpha$ 和~$\beta$ 是~$G$ 的两个~$p$-\!自同构,记~$I:=\langle\left(\alpha\beta(g)\right)\cdot\left(\beta\alpha(g)\right)^{-1}\, |\, g\in G \rangle, $ 则 \qquad (i) 当~$I$\, 是有限循环群时, $\alpha$ 和~$\beta$生成一个有限~$p$-\!群; \qquad 在下列2种情形下, ~$\alpha$ 和~$\beta$生成一个可解的剩余有限~$p$-\!群,它是有限生成的无挠幂零群被有限~$p$-\!群的扩张. \qquad (ii) 当~$I=Z_{p^{\infty}}$ 时; \qquad (iii) 当~$I=Z_{p^{m}}\oplus Z_{p^{\infty}}$ 时; \qquad 在下列4种情形下, $\alpha$ 和~$\beta$也生成一个可解的剩余有限~$p$-\!群, 它的幂零长度至多是~$3$. \qquad (iv) 当~$I$\, 是无挠的局部循环群时; \qquad (v) 当~$I$ 有子群列~$1< J< I, $其商因子分别为有限循环群、无挠的局部循环群时; \qquad (vi) 当~$I=Z_{p^{\infty}}\times J, $ 其中~$J$\,为无挠的局部循环群时; \qquad (vii) 当~$I$ 有正规列~$1< I_1研究了有限秩的幂零群的自同构, 证明了 \qquad {\heiti定理}\quad设幂零群~$G=KP$, 其中~$P$是有限秩的幂零~$p$-\!群, ~$K$ 是~$G$\,的有限秩的~$p^\prime$-\!自由的正规子群, ~$p$\, 不属于~$K$\,的谱~$S_p(K)$. 设~$\alpha$ 和~$\beta$ 是~$G$ 的两个~$p$-\!自同构,记~$I:=\langle\left(\alpha\beta(g)\right)\cdot\left(\beta\alpha(g)\right)^{-1}\, |\, g\in G \rangle, $ 则 \qquad (i) 当~$I$\, 是有限循环群时, $\alpha$ 和~$\beta$生成一个有限~$p$-\!群; \qquad 在下列2种情形下, ~$\alpha$ 和~$\beta$生成一个可解的剩余有限~$p$-\!群,它是有限生成的无挠幂零群被有限~$p$-\!群的扩张. \qquad (ii) 当~$I=Z_{p^{\infty}}$ 时; \qquad (iii) 当~$I=Z_{p^{m}}\oplus Z_{p^{\infty}}$ 时; \qquad 在下列4种情形下, $\alpha$ 和~$\beta$也生成一个可解的剩余有限~$p$-\!群, 它的幂零长度至多是~$3$. \qquad (iv) 当~$I$\, 是无挠的局部循环群时; \qquad (v) 当~$I$ 有子群列~$1< J< I, $其商因子分别为有限循环群、无挠的局部循环群时; \qquad (vi) 当~$I=Z_{p^{\infty}}\times J, $ 其中~$J$\,为无挠的局部循环群时; \qquad (vii) 当~$I$ 有正规列~$1< I_1研究了有限秩的幂零群的自同构, 证明了 \qquad {\heiti定理}\quad设幂零群~$G=KP$, 其中~$P$是有限秩的幂零~$p$-\!群, ~$K$ 是~$G$\,的有限秩的~$p^\prime$-\!自由的正规子群, ~$p$\, 不属于~$K$\,的谱~$S_p(K)$. 设~$\alpha$ 和~$\beta$ 是~$G$ 的两个~$p$-\!自同构,记~$I:=\langle\left(\alpha\beta(g)\right)\cdot\left(\beta\alpha(g)\right)^{-1}\, |\, g\in G \rangle, $ 则 \qquad (i) 当~$I$\, 是有限循环群时, $\alpha$ 和~$\beta$生成一个有限~$p$-\!群; \qquad 在下列2种情形下, ~$\alpha$ 和~$\beta$生成一个可解的剩余有限~$p$-\!群,它是有限生成的无挠幂零群被有限~$p$-\!群的扩张. \qquad (ii) 当~$I=Z_{p^{\infty}}$ 时; \qquad (iii) 当~$I=Z_{p^{m}}\oplus Z_{p^{\infty}}$ 时; \qquad 在下列4种情形下, $\alpha$ 和~$\beta$也生成一个可解的剩余有限~$p$-\!群, 它的幂零长度至多是~$3$. \qquad (iv) 当~$I$\, 是无挠的局部循环群时; \qquad (v) 当~$I$ 有子群列~$1< J< I, $其商因子分别为有限循环群、无挠的局部循环群时; \qquad (vi) 当~$I=Z_{p^{\infty}}\times J, $ 其中~$J$\,为无挠的局部循环群时; \qquad (vii) 当~$I$ 有正规列~$1< I_1其商因子分别为有限循环群、拟循环~$p$-\!群、无挠的局部循环群时. \qquad 特别地, 当群~$K$ 是一个~$FC$-\!群时, 在上述后4种情形下,~$\alpha$ 和~$\beta$生成的群也是有限生成的无挠幂零群被有限~$p$-\!群的扩张. \qquad 运用发展出来的方法, 还证明了几类有限秩的幂零群的自同构群的有限生成子群是剩余有限的.     

The adapted solution and comparison theorem for backward stochastic differential equations with Poisson jumps and applications

This paper deals with a class of backward stochastic differential equations with Poisson jumps and with random terminal times. We prove the existence and uniqueness result of adapted solution for such a BSDE under the assumption of non-Lipschitzian coefficient. We also derive two comparison theorems by applying a general Girsanov theorem and the linearized technique on the coefficient. By these we first show the existence and uniqueness of minimal solution for one-dimensional BSDE with jumps when its coefficient is continuous and has a linear growth. Then we give a general Feynman-Kac formula for a class of parabolic types of second-order partial differential and integral equations (PDIEs) by using the solution of corresponding BSDE with jumps. Finally, we exploit above Feynman-Kac formula and related comparison theorem to provide a probabilistic formula for the viscosity solution of a quasi-linear PDIE of parabolic type.     

Nonlinear Doob—Meyer Decomposition with Jumps

Concepts of g-supersolution ,g-martingale,g-supermartingale are introduced,wihch are related to BSDE with Brownian motion and Poisson Point process.A strict comparison theorem,monotonic limit theorem related to this type of BSDE are also discussed.As an application of these results,a nonlinear Doob-Meyer decomposition theorem is obtained.     

g-上鞅的Riesz分解定理

本文给出了当终端时间趋于无穷时一类有限时间区间上的倒向随机微分方程的解的收敛性,并且证明了这类解平方收敛到特定的无穷时间区间上的倒向随机微分方程的解.本文主要研究了由倒向随机微分方程生成的非线性期望及其鞅的性质,证明了当生成元g是超线性时的g-上鞅Riesz分解定理.并且指出经典鞅论中的Riesz分解定理和下期望(又称最小期望)对应的上鞅Riesz分解定理是g-上鞅Riesz分解定理的两种特殊情况.     

Optimal investment-consumption and life insurance selection problem under inflation. A BSDE approach

We discuss an optimal investment, consumption and insurance problem of a wage earner under inflation. Assume a wage earner investing in a real money account and three asset prices, namely: a real zero-coupon bond, the inflation-linked real money account and a risky share described by jump-diffusion processes. Using the theory of quadratic-exponential backward stochastic differential equation (BSDE) with jumps approach, we derive the optimal strategy for the two typical utilities (exponential and power) and the value function is characterized as a solution of BSDE with jumps. Finally, we derive the explicit solutions for the optimal investment in both cases of exponential and power utility functions for a diffusion case.     

Stochastic optimization theory of backward stochastic differential equations with jumps and viscosity solutions of Hamilton–Jacobi–Bellman equations

In this paper we study stochastic optimal control problems with jumps with the help of the theory of Backward Stochastic Differential Equations (BSDEs) with jumps. We generalize the results of Peng [S. Peng, BSDE and stochastic optimizations, in: J. Yan, S. Peng, S. Fang, L. Wu, Topics in Stochastic Analysis, Science Press, Beijing, 1997 (Chapter 2) (in Chinese)] by considering cost functionals defined by controlled BSDEs with jumps. The application of BSDE methods, in particular, the use of the notion of stochastic backward semigroups introduced by Peng in the above-mentioned work allows a straightforward proof of a dynamic programming principle for value functions associated with stochastic optimal control problems with jumps. We prove that the value functions are the viscosity solutions of the associated generalized Hamilton–Jacobi–Bellman equations with integral-differential operators. For this proof, we adapt Peng’s BSDE approach, given in the above-mentioned reference, developed in the framework of stochastic control problems driven by Brownian motion to that of stochastic control problems driven by Brownian motion and Poisson random measure.     

一类非时齐非Lipschitz条件下带跳的倒向随机微分方程的适应解及比较定理

对系数f(t,y,z,k)满足非常一般的非时齐非Lipschitz条件,本文给出一类带跳的倒向随机微分方程局部和整体解的存在唯一性的证明,同时本文也研究了带跳的倒向随机微分方程的比较定理,从而把前人的相应结果推广到更一般情形．     

Continuous dependence properties on solutions of backward stochastic differential equation

The existence theorem and continuous dependence property in ”L²” sense for solutions of backward stochastic differential equation (shortly BSDE) with Lipschitz coefficients were respectively established by Pardoux-Peng and Peng in [1,2], Mao and Cao generalized the Pardoux-Peng’s existence and uniqueness theorem to BSDE with non-Lipschitz coefficients in [3,4]. The present paper generalizes the Peng’s continuous dependence property in ”L²” sense to BSDE with Mao and Cao’s conditions. Furthermore, this paper investigates the continuous dependence property in “almost surely” sense for BSDE with Mao and Cao’s conditions, based on the comparison with the classical mathematical expectation.     

高维倒向随机微分方程比较定理

倒向随机微分方程由Pardoux和彭实戈首先提出，彭实戈给出了一维BSDE的比较定理，周海滨将其推广到了高维情形．毛学荣将倒向随机微分方程解的存在唯一性定理推广到非Lipschitz系数情况，曹志刚和严加安给了相应的一维比较定理．本文将曹志刚和严加安的比较定理推广到高维情形．     

Limit theorems for BSDE with local time applications to non-linear PDE

Given a d -dimensional Wiener process W , with its natural filtration F t , a F T -measurable random variable ξ in R , a bounded measure x on R , and an adapted process ( s , y , z ) M h ( s , y , z ), we consider the following BSDE: Y t = ξ + Z t T h ( s , Y s , Z s ) d s + Z R ( L T a ( Y ) m L t a ( Y )) x (d a ) m Z t T Z s d W s for 0 h t h T . Here L t a ( Y ) stands for the local time of Y at level a . For h =0, we establish the existence and the uniqueness of the processes ( Y , Z ), and if h is continuous with linear growth we establish the existence of a solution. We prove limit theorems for solutions of backward stochastic differential equations of the above form. Those limit theorems permit us to deduce that any solution of that equation is the limit, in a strong sense, of a sequence of semi-martingales, which are solutions of ordinary BSDEs of the form Y t = ξ + Z t T f ( Y s ) Z s 2 d s m Z t T Z s d W s . A comparison theorem for BSDEs involving measures is discussed. As an application we obtain, with the help of the connection between BSDE and PDE, some corresponding limit theorems for a class of singular non-linear PDEs and a new probabilistic proof of the comparison theorem for PDEs.     

A new existence result for quadratic BSDEs with jumps with application to the utility maximization problem

In this study, we consider the exponential utility maximization problem in the context of a jump–diffusion model. To solve this problem, we rely on the dynamic programming principle to express the value process of this problem in terms of the solution of a quadratic BSDE with jumps. Since the quadratic BSDE¹ under study is driven by both a Wiener process and a Poisson random measure having a Lévy measure with infinite mass, our main task is therefore to establish a new existence result for the specific BSDE introduced.