An Efficient Forecasting Approach to Reduce Boundary Effects in Real-Time Time-Frequency Analysis
Abstract
Time-frequency (TF) 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 approaching the boundaries of the TF domain. In this paper, 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 of the 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 performance of our approach, we validate it by implementing it on biomedical signals.
Cite
@article{arxiv.2102.07226,
title = {An Efficient Forecasting Approach to Reduce Boundary Effects in Real-Time Time-Frequency Analysis},
author = {Adrien Meynard and Hau-Tieng Wu},
journal= {arXiv preprint arXiv:2102.07226},
year = {2021}
}