Nehari函数族的偏差定理与拟共形延拓

本文讨论了Nehari函数族的偏差性质,得到了这类函数及其导数的若干偏差定理,同时研究了这类函数的拟共形延拓,并给出拟共形延拓的精确表达式.     

Nehari函数族的偏差定理与拟共形延拓

本文讨论了Nehari函数族的偏差性质,得到了这类函数及其导数的若干偏差定理,同时研究了这类函数的拟共形延拓,并给出拟共形延拓的精确表达式.     

Faber多项式及其在具有拟共形延拓的单叶函数中的应用

本文得到了关于Faber多项式的一些收敛性质并应用它们来研究具有拟共形延拓的单叶函数,特别地,通过引入l^2空间上的一个有界线性算子,可以给出单叶函数的拟共形延拓性和渐近共形性的若干刻画.     

调和映射的可积拟共形延拓

本文研究了平面调和映射的可积拟共形延拓问题.利用经典的共形映射的拟共形延拓方法和调和映射的性质,获得了一些条件使得调和映射可以拟共形延拓至整个平面且其复伸缩商关于双曲度量是p次可积的,推广了解析单叶函数的相关结果.     

有限偏差函数与调和函数

分别借助解析函数与调和函数两类函数的Dirichlet积分,利用相关文献给定边界值的拟共形映射极值伸缩商的估计方法,通过有限偏差函数和拟共形映射的关系估计了具有给定边界值的有限偏差函数的极值伸缩商.得到了解析函数的Dirichlet积分在有限偏差函数下具有拟不变性,同时给出有限偏差函数极值伸缩商的下界估计.     

关于具有拟共形扩张的比伯霸赫函数族

<正> 近十多年来,人们对具有拟共形扩张的种种单叶函数之度量的和几何的性质之研究表现了很大的兴趣,如 O.Lehto,J.O.Mcleavey,M.Schiffer 和 G.Schober 等等.本文的目的在于用具有拟共形扩张的面积原理方法,研究二类具有拟共形扩张的比伯霸赫(L.Bieberbach)函数,给出了这种函数族的 Golusin 不等式、Grunsky 不等式,指数化的 Golusin 偏差定理和 FitzGerald 不等式,以及 Schwarz 导数的估计等一系列结果.当 k→1时,它们就退化成关于比伯霸赫函数族的相应的结果[3]、[5].     

关于拟共形映照的象外之点

本文将张广厚曾研究过的三族平面拟共形映照的条件减弱,在更大、更一般的三族拟共形映照及其星(凸)象函数子族中研讨了 Szeg式问题,获得了此问题的解。     

Grunsky算子的本性模

利用一个推广的Grunsky不等式,借助于单叶函数的拟共形延拓的边界伸缩商,我们给出Grunsky算子的本性模的一些估计.作为推论,我们推出Grunsky算子的紧性准则.     

B~n上推广的Roper-Suffridge算子的性质

讨论改进后的Roper-Suffridge延拓算子保持双全纯映照子族的性质.借助双全纯映照子族的解析特征及其偏差结论,得到改进后的Roper-Suffridge延拓算子在一定条件下保持α次殆β型螺形映照、α次β型螺形映照、强β型螺形映照的性质,从而得到改进后的算子在一定条件下保持α次殆星形性、α次星形性和强星形性.所得结论为在多复变数空间中构造这些双全纯映照提供了一种新的途径.     

奇异值、拟共形映射和Schottky上界

获得了Ramanujan模方程奇异值的若干性质 (包括渐近精确的界 ) ,并由此得出了Hersch Pflugerφ-偏差函数和Agardη-偏差函数的无穷乘积表示 ,改进了显式拟共形Schwarz引理 ,获得了Schottky上界新型的渐近精确的估计 ,证实了关于线性偏差函数的一个猜测     

复杂设计下类均值复制与类加权均值复制的比较（英文）

复制数据是处理抽样调查中数据项目缺失的一种常用方法。在两种常见模型及复杂抽样设计下，本文对处理数据项目缺失的类均值复制和类加权均值复制方法进行了对比。     

Structure of Stieltjes classes of moment-equivalent probability laws

A Stieltjes class is a one-parameter family of moment-equivalent distribution functions constructed by modulation of a given indeterminate distribution function F, called the center of the class. Members of a Stieltjes class are mutually absolutely continuous, and conversely, any pair of moment-equivalent and mutually absolutely continuous distribution functions can be joined by a Stieltjes class. The center of a Stieltjes class is an equally weighted mixture of its extreme members, and this places restrictions on which distributions can belong to a Stieltjes class with a given center. The lognormal law provides interesting illustrations of the general ideas. In particular, it is possible for two moment equivalent infinitely divisible distributions to be joined by a Stieltjes class, and random scaling can be used to construct new Stieltjes classes from a given Stieltjes class.     

On blow-up regimes in one nonlinear parabolic equation

A nonlinear heat equation with a special source on a straight line is considered. The family of exact solutions to this equation that have the form p(t) + q(t)cosx/√2, where functions p(t) and q(t) satisfy a certain dynamic system, is constructed. The system is comprehensively analyzed, and the behavior of p(t) and q(t) depending on initial data is revealed. It is found that some of the unbounded solutions from the aforementioned family are close, in a certain sense, to an analytical solution to the heat equation with power nonlinearities. The Cauchy problem for the equations considered is studied as well. It is proved that, depending on the initial solution function, solutions may develop in a blow-up regime or decay.     

New efficient second derivative multistep methods for stiff systems

The aim of this paper is to select from the large family of possible general linear methods, just a single class which has considerable potential for efficient implementation. This class has possible applications depending on stiff nature of a problem to be performed. A special class of second derivative multistep method (SDMM) is derived. The stability analysis of this class which is depending on free parameters is discussed. The stability regions are plotted for certain choices of parameters. A good comparison between the results of this class and the results due to Gear and Enright is recommended during some numerical tests.     

Tomography models of random convex polygons

Combinatorial integral geometry possesses some results that can be interpreted as belonging to the field of Geometric Tomography. The main purpose of the present paper is to present a case of parallel X-ray approach to tomography of random convex polygons. However, the Introduction reviews briefly some earlier results by the author that refer to reconstruction of (non-random) convex domains by means of a point X-ray. The main tool in treating the parallel X-rays is disintegrated Pleijel identity, or rather, its averaged version, whose derivation is represented in complete detail. The paper singles out a class of random polygons called tomography models, that offer essential advantages for the analysis. The definition of a tomography model is given in terms of stochastic independence. Fortunately, random translation-invariant Poisson processes of lines in IR ² suggest a class of examples. We recall that each such line process is determined by its rose of directions ρ(?). For rather general ρ(?), the number weighted typical polygon in the polygonal partition of the plane generated by the corresponding Poisson line process happens to be a tomography model. For general tomography models, a differential equation is derived for the Laplace transform for parallel X-rays, that rises several interesting computational problems.     

Localization and residue of the Bott class

The Bott class of transversely holomorphic foliations is studied. We first introduce a formula which relates the Bott class and the Godbillon-Vey class. Then a ‘localizable part’ of the Bott class is defined. It is indeed localizable and written in terms of the Godbillon measure studied by Heitsch and Hurder. The above-mentioned formula is reviewed in terms of localizable parts. Finally, complex codimension-one foliations are considered. A version of residue is introduced and it is shown that the Bott class is ‘localized’ near the Julia set in the sense of Ghys-Gomez-Mont-Saludes. Some examples of calculation of the residue are presented.     

On a class of groups with given cofactors of maximal subgroups

The paper is devoted to the solution of the general problem of describing finite solvable groups all of whose cofactors of maximal subgroups belong to a given class $ \mathfrak{X} $ of groups. The cases in which $ \mathfrak{X} $ is a homomorph, a Schunk class, and a formation are treated separately. The approach suggested here is related to the construction of a local Schunk class defined by using a constant group function.     

When is a Coalgebra a Generator?

Let C be a coalgebra over a field k. The aim of this paper is to study the following problem : (P) If C is a k-coalgebra such that C is a generator for the category of left comodules, is C a left quasi-co-Frobenius coalgebra ? The converse always holds. We show that if C has a finite coradical series, the answer is positive.     

Porous Medium Flow with Both a Fractional Potential Pressure and Fractional Time Derivative

The authors study a porous medium equation with a right-hand side. The operator has nonlocal diffusion effects given by an inverse fractional Laplacian operator.The derivative in time is also fractional and is of Caputo-type, which takes into account"memory". The precise model isD_t~αu- div(u(-Δ)~(-σ)u) = f, 0 σ 1/2.This paper poses the problem over {t ∈ R~+, x ∈ R~n} with nonnegative initial data u(0, x) ≥0 as well as the right-hand side f ≥ 0. The existence for weak solutions when f, u(0, x)have exponential decay at infinity is proved. The main result is H¨older continuity for such weak solutions.     

Solution of the NP-hard total tardiness minimization problem in scheduling theory

The classical NP-hard (in the ordinary sense) problem of scheduling jobs in order to minimize the total tardiness for a single machine 1‖ΣT _j is considered. An NP-hard instance of the problem is completely analyzed. A procedure for partitioning the initial set of jobs into subsets is proposed. Algorithms are constructed for finding an optimal schedule depending on the number of subsets. The complexity of the algorithms is O(n ²Σp _j ), where n is the number of jobs and p _j is the processing time of the jth job (j = 1, 2, …, n).