An efficient forecasting approach to reduce boundary effects in real-time time-frequency analysis – Adrien Meynard
Adrien Meynard
Duke University, Durham
http://meynard.perso.math.cnrs.fr/
Date(s) : 15/01/2021 iCal
14h30 - 15h30
Time-frequency representations of time series are intrinsically subject to the boundary effects. As a result, the structures of signals that are highlighted by the representations are garbled when approachingthe boundaries of the TF domain. For the purpose of real-time TF information acquisition of nonstationary oscillatory time series, we propose a numerically efficient approach for the reduction of such boundary effects. The solution relies on an extension ofthe analyzed signal obtained by a forecasting technique. In the case of the study of a class of locally oscillating signals, we provide a theoretical guarantee of the performance of our approach. Following a numerical verification of the algorithmic performanceof our approach, we validate it by implementing it on biomedical signals.
Emplacement
I2M Chateau-Gombert - CMI, Salle de Séminaire R164 (1er étage)
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