An Efficient Forecasting Approach to Reduce Boundary Effects in Real-Time Time-Frequency Analysis - Archive ouverte HAL
Article Dans Une Revue IEEE Transactions on Signal Processing Année : 2021

An Efficient Forecasting Approach to Reduce Boundary Effects in Real-Time Time-Frequency Analysis

Résumé

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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Dates et versions

hal-03141062 , version 1 (14-02-2021)
hal-03141062 , version 2 (22-02-2021)

Identifiants

Citer

Adrien Meynard, Hau-Tieng Wu. An Efficient Forecasting Approach to Reduce Boundary Effects in Real-Time Time-Frequency Analysis. IEEE Transactions on Signal Processing, 2021, 69, pp.1653-1663. ⟨10.1109/TSP.2021.3062181⟩. ⟨hal-03141062v2⟩
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