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Wavelet packet transfer function modelling of nonstationary time series
Authors:Guy P Nason  Theofanis Sapatinas
Institution:(1) Institute of Biomaterials and Biomedical Engineering, University of Toronto, 164 College Street, Rosebrugh Building, Room 407, Toronto, ON, M5S 3G9, Canada;(2) Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King’s College Road, Toronto, ON, M5S 3G4, Canada;(3) Division of Fundamental Neurobiology, Toronto Western Research Institute, 399 Bathurst Street, Toronto, ON, M5T 2S8, Canada;(4) Department of Physiology, University of Toronto, 1 King’s College Circle, Toronto, ON, M5S 1A8, Canada
Abstract:This article shows how a non-decimated wavelet packet transform (NWPT) can be used to model a response time series, Y t, in terms of an explanatory time series, X t. The proposed computational technique transforms the explanatory time series into a NWPT representation and then uses standard statistical modelling methods to identify which wavelet packets are useful for modelling the response time series. We exhibit S-Plus functions from the freeware WaveThresh package that implement our methodology.The proposed modelling methodology is applied to an important problem from the wind energy industry: how to model wind speed at a target location using wind speed and direction from a reference location. Our method improves on existing target site wind speed predictions produced by widely used industry standard techniques. However, of more importance, our NWPT representation produces models to which we can attach physical and scientific interpretations and in the wind example enable us to understand more about the transfer of wind energy from site to site.
Keywords:nonstationary transfer function  nondecimated wavelet packets  wind time series  WaveThresh
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