Wavelet decomposition of forced turbulence: Applicability of the iterative Donoho-Johnstone threshold

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We examine the decomposition of forced Taylor-Green and Arn'old-Beltrami-Childress (ABC) flows into coherent and incoherent components using an orthonormal wavelet decomposition. We ask whether wavelet coefficient thresholding based on the Donoho-Johnstone criterion can extract a coherent vorte...

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Autores principales: Lord, J.W., Rast, M.P., Mckinlay, C., Clyne, J., Mininni, P.D.
Formato: Artículo publishedVersion
Lenguaje:Inglés
Publicado: 2012
Materias:
Coherent vortices
Forcings
Gaussian random noise
Gaussians
Spatial correlations
Wavelet coefficient thresholding
Gaussian distribution
Wavelet decomposition
Data compression
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_10706631_v24_n2_p_Lord
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
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spelling paperaa:paper_10706631_v24_n2_p_Lord2023-06-12T16:49:27Z Wavelet decomposition of forced turbulence: Applicability of the iterative Donoho-Johnstone threshold Phys. Fluids 2012;24(2) Lord, J.W. Rast, M.P. Mckinlay, C. Clyne, J. Mininni, P.D. Coherent vortices Forcings Gaussian random noise Gaussians Spatial correlations Wavelet coefficient thresholding Gaussian distribution Wavelet decomposition Data compression We examine the decomposition of forced Taylor-Green and Arn'old-Beltrami-Childress (ABC) flows into coherent and incoherent components using an orthonormal wavelet decomposition. We ask whether wavelet coefficient thresholding based on the Donoho-Johnstone criterion can extract a coherent vortex signal while leaving behind Gaussian random noise. We find that no threshold yields a strictly Gaussian incoherent component, and that the most Gaussian incoherent flow is found for data compression lower than that achieved with the fully iterated Donoho-Johnstone threshold. Moreover, even at such low compression, the incoherent component shows clear signs of large-scale spatial correlations that are signatures of the forcings used to drive the flows. © 2012 American Institute of Physics. Fil:Mininni, P.D. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2012 info:eu-repo/semantics/article info:ar-repo/semantics/artículo info:eu-repo/semantics/publishedVersion application/pdf eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_10706631_v24_n2_p_Lord
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
language Inglés
orig_language_str_mv eng
topic Coherent vortices
Forcings
Gaussian random noise
Gaussians
Spatial correlations
Wavelet coefficient thresholding
Gaussian distribution
Wavelet decomposition
Data compression
spellingShingle Coherent vortices
Forcings
Gaussian random noise
Gaussians
Spatial correlations
Wavelet coefficient thresholding
Gaussian distribution
Wavelet decomposition
Data compression
Lord, J.W.
Rast, M.P.
Mckinlay, C.
Clyne, J.
Mininni, P.D.
Wavelet decomposition of forced turbulence: Applicability of the iterative Donoho-Johnstone threshold
topic_facet Coherent vortices
Forcings
Gaussian random noise
Gaussians
Spatial correlations
Wavelet coefficient thresholding
Gaussian distribution
Wavelet decomposition
Data compression
description We examine the decomposition of forced Taylor-Green and Arn'old-Beltrami-Childress (ABC) flows into coherent and incoherent components using an orthonormal wavelet decomposition. We ask whether wavelet coefficient thresholding based on the Donoho-Johnstone criterion can extract a coherent vortex signal while leaving behind Gaussian random noise. We find that no threshold yields a strictly Gaussian incoherent component, and that the most Gaussian incoherent flow is found for data compression lower than that achieved with the fully iterated Donoho-Johnstone threshold. Moreover, even at such low compression, the incoherent component shows clear signs of large-scale spatial correlations that are signatures of the forcings used to drive the flows. © 2012 American Institute of Physics.
format Artículo
Artículo
publishedVersion
author Lord, J.W.
Rast, M.P.
Mckinlay, C.
Clyne, J.
Mininni, P.D.
author_facet Lord, J.W.
Rast, M.P.
Mckinlay, C.
Clyne, J.
Mininni, P.D.
author_sort Lord, J.W.
title Wavelet decomposition of forced turbulence: Applicability of the iterative Donoho-Johnstone threshold
title_short Wavelet decomposition of forced turbulence: Applicability of the iterative Donoho-Johnstone threshold
title_full Wavelet decomposition of forced turbulence: Applicability of the iterative Donoho-Johnstone threshold
title_fullStr Wavelet decomposition of forced turbulence: Applicability of the iterative Donoho-Johnstone threshold
title_full_unstemmed Wavelet decomposition of forced turbulence: Applicability of the iterative Donoho-Johnstone threshold
title_sort wavelet decomposition of forced turbulence: applicability of the iterative donoho-johnstone threshold
publishDate 2012
url http://hdl.handle.net/20.500.12110/paper_10706631_v24_n2_p_Lord
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AT clynej waveletdecompositionofforcedturbulenceapplicabilityoftheiterativedonohojohnstonethreshold
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