Integral Self-affiine Tiles of Bandt＇s Model

Integral self-affine tiling of Bandt＇s model is a generalization of the integral self-affine tiling. Using ergodic theory, we show that the Lebesgue measure of the tile is a rational number where the denominator equals to the order of the associate symmetry group. We apply the result to the study of the Levy Dragon.     

某些平均压缩迭代函数系的不变测度的L2维数的估计

假设f={f1,……,fm}是定义在R^d上的m个Lipschitz函数，形如fi(x)=λi^-1x bi(λi∈Z),假定由f产生的迭代函数系(IFS)是平均压缩的，本文给出了这种迭代函数系的不变测度的L^2-维数的上、下界的估计。     

Cantor集并的自相似性(英文)

本文研究了Cantor集和其并的自相似性.利用Cantor展式的方法,得到了关于Cantor集和迭代函数系的一个基本关系:T∪(T+α)为自相似的当且仅当存在一个非负整数n使得α=±(k2-k1)dn.进一步,若T∪(T+α)是自相似的,则它满足开集条件.     

弱分离条件下的自共形迭代函数系统

开集条件是分形几何的一个重要概念,弱分离条件(WSC)在研究有重叠的迭代函数系统(IFS)中扮演着重要角色.本文考虑满足弱分离条件的自共形迭代函数系统,并给出确定其不变集的Hausdorff维数的一种方式.     

高维分形函数与插值

1 预备知识 1986年,Barnsley[1]采用某种特殊的迭代函数系统(IFS)构造了分形插值函数(FIF), 在计算机图形学等领域得到了广泛的应用(参见[1,2,5,6])．Massopust[4],J．S．Geronimo和 D．P．Hardin[3]等构造了三角形域上的自仿射分形函数,其图像称为分形曲面。文献[7]发现了矩形区域上分形函数的特征定理,并由此解决了矩形区域的分形插值问题．本文中     

On single-matrix graph-directed iterated function systems

We study graph-directed function systems where each contraction in the system has the form fe(x)=A−1(x+de), where A is an expanding matrix. We show that a certain discreteness implies the open set condition, and the latter implies the strong open set condition. Hausdorff measures and dimensions (w.r.t. a weak norm) of the invariant sets are investigated. The stationary Markov measures of the system are proved to be translation invariant.     

A new idea to construct the fractal interpolation function

The aim of this paper is to present a new idea to construct the nonlinear fractal interpolation function, in which we exploit the Matkowski and the Rakotch fixed point theorems. Our technique is different from the methods presented in the previous literatures.     

Spectrality of certain self‐affine measures on the generalized spatial Sierpinski gasket

The self‐affine measure corresponding to a upper or lower triangle expanding matrix M and the digit set in the space is supported on the generalized spatial Sierpinski gasket, where are the standard basis of unit column vectors in . We consider in this paper the existence of orthogonal exponentials on the Hilbert space , i.e., the spectrality of . Such a property is directly connected with the entries of M and is not completely determined. For this generalized spatial Sierpinski gasket, we present a method to deal with the spectrality or non‐spectrality of . As an application, the spectral property of a class of such self‐affine measures are clarified. The results here generalize the corresponding results in a simple manner.     

On the structures of generating iterated function systems of Cantor sets

A generating IFS of a Cantor set F is an IFS whose attractor is F. For a given Cantor set such as the middle-3rd Cantor set we consider the set of its generating IFSs. We examine the existence of a minimal generating IFS, i.e. every other generating IFS of F is an iterating of that IFS. We also study the structures of the semi-group of homogeneous generating IFSs of a Cantor set F in under the open set condition (OSC). If dim_HF<1 we prove that all generating IFSs of the set must have logarithmically commensurable contraction factors. From this Logarithmic Commensurability Theorem we derive a structure theorem for the semi-group of generating IFSs of F under the OSC. We also examine the impact of geometry on the structures of the semi-groups. Several examples will be given to illustrate the difficulty of the problem we study.     

The recognition and localization of insulators adopting SURF and IFS based on correlation coefficient

The recognition and localization of insulators is a crucial process of insulators’ failure detection. Aiming to identify insulators in test aerial image under the complicated background with no template and segmentation, a novel method of the recognition and localization of insulators based on SURF (Speeded Up Robust Features) and IFS (Intuitionistic Fuzzy Set) based on correlation coefficient is proposed as following: SURF is used to extract a set of feature points of the test aerial image. Then use IFS based on correlation coefficient to partition points into k classes. Find all the connected regions for each class, and calculate minimum circumscribed rectangle and shape characteristic value for each region to identify insulators, and localize them by rectangular boxes. Thus we can detect all the insulators from test aerial image correctly. Experimental results show that the proposed approach can obtain high precision in the recognition and localization of insulators.