Math @ Duke
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Publications [#355480] of Hau-Tieng Wu
Papers Published
- Meynard, A; Wu, HT, An Efficient Forecasting Approach to Reduce Boundary Effects in Real-Time Time-Frequency Analysis,
IEEE Transactions on Signal Processing, vol. 69
(January, 2021),
pp. 1653-1663 [doi]
(last updated on 2024/04/23)
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.
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