Analysis of spherical monofractal and multifractal random fields

被引:0
|
作者
Nikolai Leonenko
Ravindi Nanayakkara
Andriy Olenko
机构
[1] Cardiff University,School of Mathematics
[2] La Trobe University,Department of Mathematics and Statistics
关键词
Rényi function; Random field; Multifractality; Monofractality; Cosmic microwave background radiation;
D O I
暂无
中图分类号
学科分类号
摘要
The Rényi function plays an important role in the analysis of multifractal random fields. For random fields on the sphere, there are three models in the literature where the Rényi function is known explicitly. The theoretical part of the article presents multifractal random fields on the sphere and develops specific models where the Rényi function can be computed explicitly. For all considered models explicit expressions of their multifractal spectrum are obtained. Properties of the models and dependencies of their characteristics on parameters are investigated. Then these results are applied to the Cosmic Microwave Background Radiation data collected from the Planck mission. The main statistical model used to describe these data in the literature is isotropic Gaussian fields. We present numerical multifractality studies and methodology based on simulating random fields, computing the Rényi function and the multifractal spectrum for different scenarios and actual CMB data. The obtained results can also find numerous potential applications for other geoscience, environmental and directional data.
引用
收藏
页码:681 / 701
页数:20
相关论文
共 50 条
  • [1] Analysis of spherical monofractal and multifractal random fields
    Leonenko, Nikolai
    Nanayakkara, Ravindi
    Olenko, Andriy
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2021, 35 (03) : 681 - 701
  • [2] Multifractal versus monofractal analysis of wetland topography
    Tchiguirinskaia, I
    Lu, S
    Molz, FJ
    Williams, TM
    Lavallée, D
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2000, 14 (01) : 8 - 32
  • [3] Multifractal versus monofractal analysis of wetland topography
    Tchiguirinskaia I.
    Lu S.
    Molz F.J.
    Williams T.M.
    Lavallée D.
    Stochastic Environmental Research and Risk Assessment, 2000, 14 (1) : 8 - 32
  • [4] Analysis of Histopathology Images by the use of Monofractal and Multifractal Algorithms
    Rajkovic, Nemanja
    Stojadinovic, Bojana
    Kranjer, Ksenija
    Radulovic, Marko
    Vukosavljevic, Dragica Nikolic
    Milosevic, Nebojsa T.
    2017 21ST INTERNATIONAL CONFERENCE ON CONTROL SYSTEMS AND COMPUTER SCIENCE (CSCS), 2017, : 350 - 355
  • [5] Monofractal and Multifractal Analysis of Discharge Signals in Transformer Pressboards
    Cekli, Serap
    Uzunoglu, Cengiz Polat
    Ugur, Mukden
    ADVANCES IN ELECTRICAL AND COMPUTER ENGINEERING, 2018, 18 (02) : 69 - 76
  • [6] Multifractal background noise of monofractal signals
    Grech, D.
    Pamula, G.
    Acta Physica Polonica A, 2012, 121 (2 B)
  • [7] Multifractal Background Noise of Monofractal Signals
    Grech, D.
    Pamula, G.
    ACTA PHYSICA POLONICA A, 2012, 121 (02) : B34 - B39
  • [8] On the multifractal effects generated by monofractal signals
    Grech, Dariusz
    Pamula, Grzegorz
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2013, 392 (23) : 5845 - 5864
  • [9] Characterization of healthy and epileptic brain EEG signals by monofractal and multifractal analysis
    Meghdadi, Amir H.
    Kinsner, Witold
    Fazel-Rezai, Reza
    2008 CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING, VOLS 1-4, 2008, : 1344 - 1348
  • [10] Multifractal to monofractal evolution of the London street network
    Murcio, Roberto
    Masucci, A. Paolo
    Arcaute, Elsa
    Batty, Michael
    PHYSICAL REVIEW E, 2015, 92 (06):