Simple Denoising Algorithm Using Wavelet Transform

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dc.creatorRoy, Manojit
dc.creatorKumar, V. Ravi
dc.creatorKulkarni, B. D.
dc.creatorSanderson, John
dc.creatorRhodes, Martin
dc.creatorStappen, Michel vander
dc.date2000-02-18
dc.date.accessioned2026-07-07T05:32:41Z
dc.date.available2026-07-07T05:32:41Z
dc.descriptionWe have presented a new and alternative algorithm for noise reduction using the methods of discrete wavelet transform and numerical differentiation of the data. In our method the threshold for reducing noise comes out automatically. The algorithm has been applied to three model flow systems - Lorenz, Autocatalator, and Rossler systems - all evolving chaotically. The method is seen to work well for a wide range of noise strengths, even as large as 10% of the signal level. We have also applied the method successfully to noisy time series data obtained from the measurement of pressure fluctuations in a fluidized bed, and also to that obtained by conductivity measurement in a liquid surfactant experiment. In all the illustrations we have been able to observe that there is a clean separation in the frequencies covered by the differentiated signal and white noise.
dc.description15 pages, 5 figures, 1 Table
dc.identifierhttps://arxiv.org/abs/nlin/0002028
dc.identifierhttp://arxiv.org/abs/nlin/0002028
dc.identifierAIChE Journal, Vol.45(11), pp 2461-2466, (1999)
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/79745
dc.subjectChaotic Dynamics
dc.titleSimple Denoising Algorithm Using Wavelet Transform
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