一类压缩型映射的不动点定理

在完备的度量空间中,讨论了一类新型的非线性压缩映射ρ(Tx,Ty)≤a(ρ(x,y))ρ(x,Tx)+b(ρ(x,y))ρ(y,Ty)+c(ρ(x,y))ρ(x,y)通过构造迭代序列,指出该映射的不动点的存在性和唯一性,并给出相应的误差估计式,拓展和改进了有关文献的范围.     

紧伪度量空间上的Hausdorff维数和加倍测度

在紧的伪度量空间(X,d)上,论证了支撑在(X,d)上的加倍测度的存在性与(X,d)上的一致度量维数之间的一些相互关系;并证明了若(X,d)有有限的一致度量维数,则对任意α>0,存在(X,d)上的加倍测度在某个Hausdorff维数最多为α的集上满测.     

基于规则的模糊信息的排序方法

以模糊数空间上的度量以及一族可以序化的模糊集(称之为规则库)为基础,引入了模糊数关于规则库的位值概念,建立了一种模糊数的排序方法,并通过模糊数关于规则库的符合度来进一步描述模糊数关于规则库的位值,给出了模糊信息的复合量化策略,讨论了位值和符合度的基本性质,为有效地解决某种意识下的不确定型优化问题奠定了基础.     

Generalized Einstein manifolds

A Finslerian manifold is called a generalized Einstein manifold (GEM) if the Ricci directional curvature R(u,u) is independent of the direction. Let F⁰(M, g_t) be a deformation of a compact n-dimensional Finslerian manifold preserving the volume of the unitary fibre bundle W(M). We prove that the critical points g₀ F⁰(g_t) of the integral I(g_t) on W(M) of the Finslerian scalar curvature (and certain functions of the scalar curvature) define a GEM. We give an estimate of the eigenvalues of Laplacian Δ defined on W(M) operating on the functions coming from the base when (M, g) is of minima fibration with a constant scalar curvature H admitting a conformal infinitesimal deformation (CID). We obtain λ ≥ H/(n − 1) (Δf = λf). If M is simply connected and λ = H/(n − 1), then (M, g) is Riemannian and is isometric to an n-sphere. We first calculate, in the general case, the formula of the second variationals of the integral I (g_t) for G = g₀, then for a CID we show that for certain Finslerian manifolds, I″(g₀) > 0. Applications to the gravitation and electromagnetism in general relativity are given. We prove that the spaces characterizing Einstein-Maxwell equations are GEMs.     

Boundary behavior of harmonic functions on metric measure spaces with non-negative Ricci curvature

Let (X, d, μ) be a metric measure space with non-negative Ricci curvature. This paper is concerned with the boundary behavior of harmonic function on the (open) upper half-space X\times {\text{ℝ}}_{+}. We derive that a function f of bounded mean oscillation (BMO) is the trace of harmonic function u(x,t) on X\times {\text{ℝ}}_{+},u(x,0)=f\left(x\right), whenever u satisfies the following Carleson measure condition where \nabla =({\nabla }_x,{\partial }_t) denotes the total gradient and B(x_B,r_B) denotes the (open) ball centered at x_B with radius r_B. Conversely, the above condition characterizes all the harmonic functions whose traces are in BMO space.     

Self-intersecting geodesics and entropy of the geodesic flow

Given a symmetric Finsler metric on T^2 whose geodesic flow has zero topological entropy, we show that the lift in the universal covering R^2 →T^2 of any closed geodesic on T^2 must be an embedded curve in R^2.     

90年代的广义度量空间理论

广义度量空间理论是一般拓扑学研究的重要课题。本文综述了90年代广义度量空间理论的成就，分析了它的主要研究课题，所取得的重要结果是国内学者在该方向的贡献。     

On doubly warped product Finsler manifolds

In this paper, we introduce horizontal and vertical warped product Finsler manifolds. We prove that every C-reducible or proper Berwaldian doubly warped product Finsler manifold is Riemannian. Then, we find the relation between Riemannian curvatures of doubly warped product Finsler manifold and its components, and consider the cases that this manifold is flat or has scalar flag curvature. We define the doubly warped Sasaki-Matsumoto metric for warped product manifolds and find a condition under which the horizontal and vertical tangent bundles are totally geodesic. We obtain some conditions under which a foliated manifold reduces to a Reinhart manifold. Finally, we study an almost complex structure on the tangent bundle of a doubly warped product Finsler manifold.     

Scenario Reduction Algorithms in Stochastic Programming

We consider convex stochastic programs with an (approximate) initial probability distribution P having finite support supp P, i.e., finitely many scenarios. The behaviour of such stochastic programs is stable with respect to perturbations of P measured in terms of a Fortet-Mourier probability metric. The problem of optimal scenario reduction consists in determining a probability measure that is supported by a subset of supp P of prescribed cardinality and is closest to P in terms of such a probability metric. Two new versions of forward and backward type algorithms are presented for computing such optimally reduced probability measures approximately. Compared to earlier versions, the computational performance (accuracy, running time) of the new algorithms has been improved considerably. Numerical experience is reported for different instances of scenario trees with computable optimal lower bounds. The test examples also include a ternary scenario tree representing the weekly electrical load process in a power management model.     

一种基于度量距离学习的图像检索方法

CBIR系统由于受图像低层特征的限制,制约了它的检索效果。机器学习和统计方法是一种有效的提高检索性能的方法,但通常需要大量的训练样本才能达到满意的检索精度。提出一种理想的距离度量函数,在对图像进行简单分类并提供少量训练样本的基础上,通过类的距离度量矩阵M的学习来考虑分量之间的相关性。这个度量导入二次最佳化问题的解,将训练样本类结构的倾斜最小化。试验结果表明,该方法能在学习样本极少的情况下提高检索的性能。