Wavelet decomposition of forced turbulence: Applicability of the iterative Donoho-Johnstone threshold
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: | , , , , |
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| Formato: | Artículo publishedVersion |
| Publicado: |
2012
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| Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_10706631_v24_n2_p_Lord https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=artiaex&d=paper_10706631_v24_n2_p_Lord_oai |
| Aporte de: |
| Sumario: | 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. |
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