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Fractals pp 47–64Cite as

Wavelets for Scaling Processes

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Abstract

Depending on the considered range of scales, different scaling processes may be defined, which correspond to different situations connected with self-similarity, fractality or long-range dependence. Wavelet analysis is shown to offer a unified framework for dealing with such processes and estimating the corresponding scaling parameters. Estimators are proposed and discussed on the basis of representations in the wavelet domain. Statistical (and computational) efficiency can be obtained not only for second-order processes, but also for linear fractional stable motions with infinite variance.

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Author information

Authors and Affiliations

  1. Ecole Normale Supérieure de Lyon, Laboratoire de Physique (Umr 5672 Cnrs), 46 allée d’Italie, 69364, Lyon Cedex 07, France

    Patrick Flandrin & Patrice Abry

Authors
  1. Patrick Flandrin
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  2. Patrice Abry
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Editor information

Editors and Affiliations

  1. Faculty of Technical Mathematics aus SC, Delft University of Technology, Melalweg 4, 2628 CD, Delft, The Netherlands

    Michel Dekking

  2. INRIA, Rocquencourt, B.P. 105, 78153, Le Chesnay Cedex, France

    Jacques Lévy Véhel  & Evelyne Lutton  & 

  3. Université Blaise Pascal, Département Mathématiques, 63177, Aubière Cedex, France

    Claude Tricot

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© 1999 Springer-Verlag London Limited

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Flandrin, P., Abry, P. (1999). Wavelets for Scaling Processes. In: Dekking, M., Véhel, J.L., Lutton, E., Tricot, C. (eds) Fractals. Springer, London. https://doi.org/10.1007/978-1-4471-0873-3_4

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  • DOI: https://doi.org/10.1007/978-1-4471-0873-3_4

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-1225-9

  • Online ISBN: 978-1-4471-0873-3

  • eBook Packages: Springer Book Archive

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