Retrieving sinusoids from nonuniformly sampled data using recursive formulations

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• 作者：Ivan Maric ^{ivan.maric@irb.hr}
• 关键词：Signal decomposition ; Signal recovery ; Sparse set of sinusoids ; Time series modeling ; Predictive least squares
• 刊名：Expert Systems with Applications
• 出版年：2017
• 出版时间：15 April 2017
• 年：2017
• 卷：72
• 期：Complete
• 页码：245-257
• 全文大小：1629 K
• 卷排序：72

文摘

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.