μ-统计自仿射集的Hausdorff维数估计

本文定义了一类μ－统计自仿射集,得到了其Hausdorff维数的上下估计Falconer定义的(严格)自仿射集及Graf定义的统计自相似情形均为本文特例     

多型随机递归集关于统计自相似测度的Multifractal分解

本文构造了一类多型随机递归集Ｋ,并利用 Ｆａｌｃｏｎｅｒ的方法［１］获得了Ｋ的重分形分解集Ｋａ（ａ＞０）的Ｈａｕｓｄｏｒｆｆ维数和Ｐａｃｋｉｎｇ维数．     

有限域上的仿射辛空间及其应用

本文中，首先给出了有限域Ｆｑ上的２ｖ维仿射辛空间ＡＳＧ（２ｖ，Ｆｑ）和２ｖ次仿射辛群ＡＳｐ２ｖ（Ｆｑ）的概念，然后讨论ＡＳｐ２ｖ（Ｆｑ）作用在ＡＳＧ（２ｖ，Ｆｑ）上的可迁性及一些相关的计数定理，最后给出应用仿射辛空间构作结合方案和认证码的例子。     

统计自相似集和测芳的概率特征

证明了统计自相似集和测度是由一族独立同分布的随机压缩算子所构成的随机递归集和它的分布，此处ｆ０是概率空间（Ω，Ｆ，Ｐ）到ｃｏｍ（Ｅ）的随机元，而ｃｏｎ（Ｅ）是完备可分距离空间Ｅ到Ｅ的压缩算子全体。     

广义自相似集的维数研究

广义自相似集的维数研究华苏（清华大学应用数学系，北京１０００８４）ＯＮＴＨＥＤＩＭＥＮＳＩＯＮＯＦＧＥＮＥＲＡＬＩＺＥＤＳＥＬＲ－ＳＩＭＩＬＡＲＳＥＴＳ￥ＨＵＡＳＵ（ＤｅｐａｒｔｍｅｎｔｏｆＡｐｐｌｉｅｄＭａｔｈｅｍａｔｉｃｓ，ＴｓｉｎｇｈｕａＵｎｉ...     

体上的矩阵方程AX~＊－XB＝C与AX±XB＝_＋~－C

设Ｆ和Ω分别是一个任意的体和一个具有对合反自同构的有限维中心代数且ｃｈａｒΩ≠２．本文研究体上的下列矩阵方程：分别给出了在Ω上（１）有一般解，（２）有自共轭解及（３）有斜自共轭解的充要条件，并将Ｗ．Ｅ．Ｒｏｔｈ的相似定理推广到了任意的体Ｆ上．     

由表示系统生成的分形的维数

在这篇文章里,由Ｒｎ中点的表示系统所生成的自仿射集中,给出了自仿射集满足Ｍｏｒａｎ开集条件的一个新的判别方法和不满足开集条件的自相似集的Ｈａｕｓｄｏｒｆｆ维数的上界和下界,并根据两个实例估计出其上下界是相等的．     

SOME RESULTS ON ESTIMATION OF THE TAIL INDEX OF A DISTRIBUTION

§１．ＩｎｔｒｏｄｕｃｔｉｏｎＳｕｐｐｏｓｅｔｈａｔＦｉｓａｄｉｓｔｒｉｂｕｔｉｏｎｆｕｎｃｔｉｏｎｓｕｃｈｔｈａｔ,ｆｏｒａｎｙｘ＞０,ｌｉｍｔ→∞１－Ｆ（ｔｘ）１－Ｆ（ｔ）＝ｘ－１γ,γ＞０．（１．１）ＷｅｃａｌγｔｈｅｔａｉｌｉｎｄｅｘｏｆＦ．...     

差异张量平行和半平行的仿射超曲面

本文用活动标架法证明了：若 Ｍｎ（ｎ≥２）是 ｎ＋１维仿射空间 Ａｎ＋１中非退化的仿射超曲面,（１）若■Ｋ＝０（即差异张量平行）,则Ｍ是仿射球,且Ｊ＝０和Ｇ是一个Ｅｉｎｓｔｅｉｎ度量,这里Ｊ是Ｍ的 Ｐｉｃｋ不变量,Ｇ是Ｂｌａｓｃｈｋｅ度量;（２）Ｒ·Ｋ＝０（即差异张量半平行）当且仅当Ｓ＝０（Ｍ为虚仿射球）,或者Ｋ＝０（Ｍ为非退化的二次超曲面）,这里 Ｒ为诱导仿射联络 ■的黎曼曲率算子．     

A1型扩张仿射Lie代数的分次自同构群

文献[1]从Euclid空间R^v（v≥1）的一个半格S出发,定义了一个Jordan代数J（S）：然后通过Tits—Kantor-Koecher方法由J（S）构造出Lie代数G（J（S））．最后利用G（J（S））得到A1型扩张仿射Lie代数L（J（S））．本文给出v=2,S为格时。A1型扩张仿射Lie代数L（J（S））的Z^2一分次自同构群．     

Elementary density bounds for self-similar sets and application

Falconer[1] used the relationship between upper convex density and upper spherical density to obtain elementary density bounds for s-sets at H S-almost all points of the sets. In this paper, following Falconer[1], we first provide a basic method to estimate the lower bounds of these two classes of set densities for the self-similar s-sets satisfying the open set condition （OSC）, and then obtain elementary density bounds for such fractals at all of their points. In addition, we apply the main results to the famous classical fractals and get some new density bounds.     

Random Markov-self-similar measures

Fractals and measures are often defined in a constructive way. In this paper, we give the construction of random measures concentrated on random Markov-self-similar fractals and prove that under quite weak conditions random Markov-self-similar measures exist and satisfy certain self-similarity property.     

Random recursive construction of self-similar fractal measures. The noncompact case

Summary The self-similarity of sets (measures) is often defined in a constructive way. In the present paper it will be shown that the random recursive construction model of Falconer, Graf and Mauldin/Williams for (statistically) self-similar sets may be generalized to the noncompact case. We define a sequence of random finite measures, which converges almost surely to a self-similar random limit measure. Under certain conditions on the generating Lipschitz maps we determine the carrying dimension of the limit measure.     

Random point fields with Markovian refinements and the geometry of fractally disordered media

We give a general construction of the probability measure for describing stochastic fractals that model fractally disordered media. For these stochastic fractals, we introduce the notion of a metrically homogeneous fractal Hansdorff-Karathéodory measure of a nonrandom type. We select a classF[q] of random point fields with Markovian refinements for which we explicitly construct the probability distribution. We prove that under rather weak conditions, the fractal dimension D for random fields of this class is a self-averaging quantity and a fractal measure of a nonrandom type (the Hausdorff D-measure) can be defined on these fractals with probability 1. Translated from Teoreticheskaya i Matematicheskaya Fizika, Vol. 124, No. 3, pp. 490–505, September, 2000.     

一般随机缺项三角级数表示断片的Bouligand维数

该文对［１］中的Ｂｏｕｌｉｇａｎｄ维数计算公式进行了改进，用对称原理和简化原理，得到了一般随机缺项三角级数所表示断片的Ｂｏｕｌｉｇａｎｄ维数的一些计算公式．     

On the description of self-similarity for attractors by means of conditional entropy

There exist several sets having similar structure on arbitrarily small scales. Mandelbrot called such sets fractals, and defined a dimension that assigns non-integer numbers to fractals. On the other hand, a dynamical system yielding a fractal set referred to as a strange attractor is a chaotic map. In this paper, a characterization of self-similarity for attractors is attempted by means of conditional entropy.     

Weak Uncertainty Principles on Fractals

We use the analytic tools such as the energy, and the Laplacians defined by Kigami for a class of post-critically finite (pcf) fractals which includes the Sierpinski gasket (SG), to establish some uncertainty relations for functions defined on these fractals. Although the existence of localized eigenfunctions on some of these fractals precludes an uncertainty principle in the vein of Heisenberg’s inequality, we prove in this article that a function that is localized in space must have high energy, and hence have high frequency components. We also extend our result to functions defined on products of pcf fractals, thereby obtaining an uncertainty principle on a particular type of non-pcf fractal.     

Discrete characterisations of Lipschitz spaces on fractals

A. Kamont has discretely characterised Besov spaces on intervals. In this paper, we give a discrete characterisation of Lipschitz spaces on fractals admitting a type of regular sequence of triangulations, and for a class of post critically finite self‐similar sets. This shows that on some fractals, certain discretely defined Besov spaces, introduced by R. Strichartz, coincide with Lipschitz spaces introduced by A. Jonsson and H. Wallin for low order of smoothness. (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

相应于随机自相似分形的记忆函数和分数次积分

For a physics system which exhibits memory, if memory is preserved only at points of random self-similar fractals, we define random memory functions and give the connection between the expectation of flux and the fractional integral. In particular, when memory sets degenerate to Cantor type fractals or non-random self-similar fractals our results coincide with that of Nigmatullin and Ren et al. .     

Products of random matrices and derivatives on p.c.f. fractals

We define and study intrinsic first order derivatives on post critically finite fractals and prove differentiability almost everywhere with respect to self-similar measures for certain classes of fractals and functions. We apply our results to extend the geography is destiny principle to these cases, and also obtain results on the pointwise behavior of local eccentricities on the Sierpiński gasket, previously studied by Öberg, Strichartz and Yingst, and the authors. We also establish the relation of the derivatives to the tangents and gradients previously studied by Strichartz and the authors. Our main tool is the Furstenberg-Kesten theory of products of random matrices.