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In Chapter 1, we introduce the definitions of Hausdorff dimension and Hausdorff measure, and some related definitions and theorems.

第一章介绍Hausdorff维数和Hausdorff测度的定义及一些相关的定义和定理。

In precise, we obtain the exact Hausdorff measure functions for level sets of N-parameter symmetric stable processes.

具体来说,我们得到了对称稳定过程的水平集的确切Hausdorff测度函数。

Another problem he did not answer is the Hausdorff dimension and the exact Hausdorff measure functions for level sets of this processes.

为比较起见,我们回顾了一些相关过程的水平集的Hausdorff测度函数的解决过程。

Hausdorff distance is a popular measure between two sets of points, and has been widely used in object matching, tracking and recognition.

Hausdorff距离(Hausdorff distance, HD)是一种点集与点集之间的距离测度,常用于目标物体的匹配、跟踪和识别等。

The existence of its multiple points is proved by means of getting Holder condition of its self-intersection local time and the lower bounds are obtained about the Hausdorff dimension and measure of its multiple times.

lder条件的讨论,证明了其重点的存在性,得到了广义α-stable过程多重时的Hausdorff维数及测度的下界。

In chapter 3, the convergence, Hausdorff dimension and measure about random recursive sets are investigated after establishing a general definition of these sets.

第三章从广泛的角度定义了随机递归集,并研究了其收敛性和Hausdor任维数与测度

By the partial estimate principle established in Ref. [46] and the special structure of the self-similar sets, we can get a better upper bound of the Hausdorff measure by means of a better covering set.

主要是利用文[46]中的部分估计原理,同时结合所考虑的自相似集的特殊结构,寻找一个较好的覆盖集合,得出其Hausdorff测度的一个上界。

Improved Hausdorff distance is used to measure the similarity between seals,as seal quality being the control parameters.

把印鉴质量指标作为MS与SS对应边缘Hausdorff距离测度的控制参数,用神经网络方法综合分析、判别印鉴真伪。

By formulating the growth of the Local times, we thus obtain the lower bounds of the Hausdorff measure functions for the level sets of strictly stable processes.

进一步,我们考虑了该局部时的增量的变化率,从而获得了水平集的Hausdorff测度函数下界。

W. Ehm gave this stochastic processes in 1981, and he obtained most of the exact Hausdorff measure functions for the sets of the range and graph of the processes, excluding some special cases, i.

Ehm在1981年给出了这类过程的定义,并得到了除一些特殊情况(即当稳定过程所在的参数空间的维数与它的特征指标的乘积恰好与稳定过程所取值的空间的维数相等)外,该过程的像集和图集的确切Hausdorff测度函数。W。

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