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Scaling and Wavelets: An Introductory Walk

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Book cover Processes with Long-Range Correlations

Part of the book series: Lecture Notes in Physics ((LNP,volume 621))

Abstract

This chapter offers, first, an introductory walk through the notions related to scaling phenomena and intuitions behind are gathered to formulate a tentative definition. Second, it introduces the mathematical model of self-similar processes with stationary increments, understood as the canonical reference to describe scaling. Then, it shows how and why the wavelet transform constitutes a powerful and relevant tool for the analysis (detection, identification, estimation) of self-similarity. It is finally explained why self-similarity is too restrictive a model to account for the large variety of scaling encountered in empirical data and a review of the various models related to scaling— long range dependence, local Hölder regularity, fractal and multifractal processes, multiplicative or cascade processes— is proposed. Their interrelations and differences, as well as estimation issues, are discussed. A set of Matlab routines has beendev eloped to implement the wavelet-based analysis for scaling described here. It is available at www.ens-lyon.fr/~pabry.

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Abry, P. (2003). Scaling and Wavelets: An Introductory Walk. In: Rangarajan, G., Ding, M. (eds) Processes with Long-Range Correlations. Lecture Notes in Physics, vol 621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44832-2_3

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  • DOI: https://doi.org/10.1007/3-540-44832-2_3

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  • Print ISBN: 978-3-540-40129-2

  • Online ISBN: 978-3-540-44832-7

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