Retrieving sinusoids from nonuniformly sampled data using recursive formulations
作者:
Highlights:
• A recursive formulation is used to retrieve sinusoids from nonuniformly sampled data.
• The approach combines EDC-type estimators to select the number of sinusoids.
• The algorithm enables to retrieve the frequencies above the Nyquist frequency.
• The procedure can efficiently model a time series with linear trend in data.
• The approach achieves the Cramer–Rao lower bound above the threshold SNR.
摘要
•A recursive formulation is used to retrieve sinusoids from nonuniformly sampled data.•The approach combines EDC-type estimators to select the number of sinusoids.•The algorithm enables to retrieve the frequencies above the Nyquist frequency.•The procedure can efficiently model a time series with linear trend in data.•The approach achieves the Cramer–Rao lower bound above the threshold SNR.
论文关键词:Signal decomposition,Signal recovery,Sparse set of sinusoids,Time series modeling,Predictive least squares
论文评审过程:Received 18 March 2016, Revised 27 October 2016, Accepted 27 October 2016, Available online 29 October 2016, Version of Record 2 January 2017.
论文官网地址:https://doi.org/10.1016/j.eswa.2016.10.057