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Large scale behavior of wavelet coefficients of non-linear subordinated processes with long memory

Abstract : We study the asymptotic behavior of wavelet coefficients of random processes with long memory. These processes may be stationary or not and are obtained as the output of non--linear filter with Gaussian input. The wavelet coefficients that appear in the limit are random, typically non--Gaussian and belong to a Wiener chaos. They can be interpreted as wavelet coefficients of a generalized self-similar process.
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Submitted on : Friday, June 11, 2010 - 10:15:13 AM
Last modification on : Wednesday, March 23, 2022 - 3:50:06 PM
Long-term archiving on: : Friday, September 17, 2010 - 1:49:50 PM

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Marianne Clausel, François Roueff, Murad Taqqu, Ciprian Tudor. Large scale behavior of wavelet coefficients of non-linear subordinated processes with long memory. Applied and Computational Harmonic Analysis, Elsevier, 2012, 32 (2), pp.223-241. ⟨10.1016/j.acha.2011.04.003⟩. ⟨hal-00491303⟩

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