R~d中无界子集的离散填充指标(I)(英文)

本文定义了 Rd 中无界集合上的几种离散填充指标 ,并得到了若干性质 .特别地 ,对任意给定的非空集合 A Rd 和任意正整数 m,dim( m )P (A) =d* im( m )P (A) =d～ im( m )P (A) =d～ im( m )P ((A) ) =dim( m )P ((A) ) =dim( 2 )P ((A) ) .     

Zd中离散分形指标的线性不变性质

研究欧几里得格 Zd 内离散分形指标的线性不变性质 ,即证明了上、下离散质量维数的线性不变性质 ,离散 Hausdorff维数的线性不变性质以及离散填充维数的线性不变性质 .     

Rd中无界子集的离散填充指标(Ⅰ)

本文定义了R^d中无界集合上的几种离散填充指标，并得到了若干性质，特别地，对任意给定的非空集合A属于R^d和任意正整数m，d^-imp^(m)(A)=dimp^(m)(A)=d^～imp^(m)(A^)=d^～imp^(m)（φ（A））=dimp^(m)(φ（A））=dimp^(2)(φ（A））。     

关于Subordinator的指数与维数

设X(t)是R^d(d为正整数)中的Levy过程，本文首先对前人所定义的X(t)的各种指数给出了另外一种刻划，事实上它们可以用极限的形式表达．这种刻划使得这些指数的几何意义非常明确．且适合于构造各种各样的例子，若X(t)是一个Subordinator，本文证明了X(t)的象集的填充维数就是X(t)的上指数β，并且举例说明存在Subordinator，它的象集的Hausdorff维数为0而填充维数为1.     

关于对偶扩张代数有限维数的注记

没A是一个有限维代数，R为A的对偶扩张代数．本我们讨论R的有限维数findim R of R，证明了，在—般情况下findim R≠2findim A，这就回答了惠昌常教授所提的一个问题．     

关于不变集的一个注记

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自相似测度的联合发散点和填充维数

近年来,发散点引起了数学界的广泛关注,对单测度的发散点,前人已经作了很完备的研究,对有限多个自相似测度的联合发散点的集合,仅其豪斯多夫维数被L．Olsen研究并给出了,然而,我们对其填充维数仍一无所知,因此,本文主要研究联合发散点集合的填充维数。     

关于Gorenstein投射维数的一个注记

本文研究了Gorenstein投射维数的相关问题.利用经典同调维数的研究方法,给出了Gorenstein投射维数有限模的Gorenstein投射维数的一个刻画,并利用这一结果证明了Gorenstein完全环和Artin环的Gorenstein整体维数分别由各自的循环模和单模的Gorenstein投射维数来确定.这些结论丰富了Gorenstein同调代数理论.     

自相似测度的联合发散点和填充维数(英文)

近年来,发散点引起了数学界的广泛关注.对单测度的发散点,前人已经作了很完备的研究.对有限多个自相似测度的联合发散点的集合,仅其豪斯多夫维数被L.Olsen研究并给出了,然而,我们对其填充维数仍一无所知.因此,本文主要研究联合发散点集合的填充维数.     

关于二次型零点的注记

给出复系数和实系数n元二次型零点向量组的秩,以及最大零点子空间的维数.证明了正负惯性指数为p,q的实二次型的最大零点子空间的维数为n-max{p,q},以及秩为r的复二次型的最大零点子空间的维数为■.     

Billingsley's packing dimension

For a stochastic process on a finite state space, we define the notion of a packing measure based on the naturally defined cylinder sets. For any two measures , , corresponding to the same stochastic process, if

then we prove that

     

A note on multifractal packing dimension of measures

The relations between the multifractal packing dimension of Borel probability measures and the asymptotic behavior of the function φ*(x) = lim sup r→0 logν(B(x,r)) - qlogμ(B(x,r)) logr are discussed and some applications are given.     

Exact packing dimension in random recursive constructions

We explore the exact packing dimension of certain random recursive constructions. In case of polynomial decay at 0 of the distribution function of random variable X, associated with the construction, we prove that it does not exist, and in case of exponential decay it is t|log|logt||, where is the fractal dimension of the limit set and 1/ is the rate of exponential decay.Research supported by the Department of Mathematics and Statistics (Mathematics) at University of Jyväskylä.Mathematics Subject Classification (2000):Primary 28A78, 28A80; Secondary 60D05, 60J80     

A heuristic for the three-dimensional strip packing problem

The contribution presents a heuristic for the three-dimensional strip packing problem (3D-SPP) with rectangular pieces (boxes). The considered 3D-SPP can be formulated as follows: for a given set of boxes and a given longitudinal open container, determine an arrangement of all boxes within the container so that the required container length is minimized.     

Constructions of optimal packing designs

Let v and k be positive integers. A (v, k, 1)-packing design is an ordered pair (V, B) where V is a v-set and B is a collection of k-subsets of V (called blocks) such that every 2-subset of V occurs in at most one block of B. The packing problem is mainly to determine the packing number P(k, v), that is, the maximum number of blocks in such a packing design. It is well known that P(k, v) ≤ ⌊v⌊(v − 1)/(k − 1)⌋/k⌋ = J(k, v) where ⌊×⌋ denotes the greatest integer y such that y ≤ x. A (v, k, 1)-packing design having J(k, v) blocks is said to be optimal. In this article, we develop some general constructions to obtain optimal packing designs. As an application, we show that P(5, v) = J(5, v) if v ≡ 7, 11 or 15 (mod 20), with the exception of v ∈ {11, 15} and the possible exception of v ∈ {27, 47, 51, 67, 87, 135, 187, 231, 251, 291}. © 1998 John Wiley & Sons, Inc. J Combin Designs 6: 245–260, 1998     

Uniform packing dimension results for multiparameter stable processes

In this article, authors discuss the problem of uniform packing dimension of the image set of multiparameter stochastic processes without random uniform H(o)lder condition, and obtain the uniform packing dimension of multiparameter stable processes.If Z is a stable (N, d, α)-process and αN ≤ d, then the following holds with probability 1 Dim Z(E) = α DimE for any Borel setE ∈ B(R N),where Z(E) = {x: (E) t ∈ E, Z(t) = x}. Dim(E) denotes the packing dimension of E.     

New and improved level heuristics for the rectangular strip packing and variable-sized bin packing problems

We consider two types of orthogonal, oriented, rectangular, two-dimensional packing problems. The first is the strip packing problem, for which four new and improved level-packing algorithms are presented. Two of these algorithms guarantee a packing that may be disentangled by guillotine cuts. These are combined with a two-stage heuristic designed to find a solution to the variable-sized bin packing problem, where the aim is to pack all items into bins so as to minimise the packing area. This heuristic packs the levels of a solution to the strip packing problem into large bins and then attempts to repack the items in those bins into smaller bins in order to reduce wasted space. The results of the algorithms are compared to those of seven level-packing heuristics from the literature by means of a large number of strip-packing benchmark instances. It is found that the new algorithms are an improvement over known level-packing heuristics for the strip packing problem. The advancements made by the new and improved algorithms are limited in terms of utilised space when applied to the variable-sized bin packing problem. However, they do provide results faster than many existing algorithms.