An efficient forecasting approach to reduce boundary effects in real-time time-frequency analysis – Adrien Meynard

Adrien Meynard
Duke University, Durham

Date(s) : 15/01/2021   iCal
14 h 30 min - 15 h 30 min

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.

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