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Convergence in L p ([0, T]) of Wavelet Expansions of φ-Sub-Gaussian Random Processes

Author

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  • Yuriy Kozachenko

    (Kyiv University)

  • Andriy Olenko

    (La Trobe University)

  • Olga Polosmak

    (Kyiv University)

Abstract

The article presents new results on convergence in L p ([0,T]) of wavelet expansions of φ-sub-Gaussian random processes. The convergence rate of the expansions is obtained. Specifications of the obtained results are discussed.

Suggested Citation

  • Yuriy Kozachenko & Andriy Olenko & Olga Polosmak, 2015. "Convergence in L p ([0, T]) of Wavelet Expansions of φ-Sub-Gaussian Random Processes," Methodology and Computing in Applied Probability, Springer, vol. 17(1), pages 139-153, March.
    • Handle: RePEc:spr:metcap:v:17:y:2015:i:1:d:10.1007_s11009-013-9346-7
    DOI: 10.1007/s11009-013-9346-7
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    References listed on IDEAS

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    1. Bardet, J.-M. & Tudor, C.A., 2010. "A wavelet analysis of the Rosenblatt process: Chaos expansion and estimation of the self-similarity parameter," Stochastic Processes and their Applications, Elsevier, vol. 120(12), pages 2331-2362, December.
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    Cited by:

    1. Nour Al Hayek & Illia Donhauzer & Rita Giuliano & Andriy Olenko & Andrei Volodin, 2022. "Asymptotics of Running Maxima for φ-Subgaussian Random Double Arrays," Methodology and Computing in Applied Probability, Springer, vol. 24(3), pages 1341-1366, September.

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