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
