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On the Choice of Thresholding Parameters for Non-Gaussian Noise Distribution

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The paper considers the problem of estimating the signal function from noisy observations using threshold processing of its wavelet expansion coefficients. Under general assumptions about the properties of the noise distribution, the asymptotic order of the optimal threshold is calculated, minimizing the loss function, based on the probability that the maximum error in the wavelet coefficients exceeds a given critical level.

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Authors and Affiliations

  1. Department of Mathematical Statistics, Faculty of Computational Mathematics and Cybernetics, M. V. Lomonosov Moscow State University, Moscow, Russia

    A. A. Kudryavtsev & O. V. Shestakov

  2. Institute of Informatics Problems, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Moscow, Russia

    O. V. Shestakov

Authors
  1. A. A. Kudryavtsev
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  2. O. V. Shestakov
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Correspondence to A. A. Kudryavtsev.

Additional information

Proceedings of the XXXV International Seminar on Stability Problems for Stochastic Models, Perm, Russia, September 24–28, 2018. Part I.

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Kudryavtsev, A.A., Shestakov, O.V. On the Choice of Thresholding Parameters for Non-Gaussian Noise Distribution. J Math Sci 246, 519–524 (2020). https://doi.org/10.1007/s10958-020-04756-7

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  • DOI: https://doi.org/10.1007/s10958-020-04756-7

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