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Multiscale representation and estimation of fractal point processes

机译:分形过程的多尺度表示和估计

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Fractal point processes have a potentially important role to play in the modeling of a wide range of natural and man-made phenomena. However, the lack of a suitable framework for their representation has frequently made their application in many problems difficult. We introduce natural multiscale representations for an important class of these processes based on mixtures of Poisson processes. In turn, this framework leads to efficient new algorithms for both the synthesis and the analysis of such processes. These include algorithms for optimal fractal dimension and interarrival time estimation that are of interest in a range of applications. Several aspects of the performance of these algorithms are also addressed.
机译:分形点过程在各种自然和人为现象的建模中具有潜在的重要作用。但是,由于缺乏合适的表示框架,经常使它们在许多问题上的应用变得困难。我们基于泊松过程的混合为这些过程的重要类别引入自然的多尺度表示。反过来,此框架导致了用于此类过程的综合和分析的高效新算法。这些包括用于最佳分形维数和到达间隔时间估计的算法,这些算法在一系列应用中都受到关注。还讨论了这些算法性能的几个方面。

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