On the Choice of Sampling Rates in Parametric Identification of Time Series

Summary, in English

Aliasing gives a lower bound for the sampling rate in ordinary spectral analysis of a time series. In parametric it appears at first sight that no such limitations are present. In this note we will obtain insight into this paradox by analyzing a simple Gauss-Markov process. We assume that a time series analysis is performed based on N samples of the series at equal spacing h. The result shows that there is an optimal choice of h and that the variance increases rapidly when h increases from the optimal value. The analysis of a time series of fixed length T with different number of samplings is also discussed.

• Author: Karl Johan Åström
• Department/s: Department of Automatic Control
• Publishing year: 1969
• Language: English
• Pages: 273-278
• Publication/Series: Information Sciences
• Volume: 1
• Issue: 3
• Links: http://dx.doi.org/10.1016/S0020-0255(69)80013-7
• Document type: Journal article
• Publisher: Elsevier
• Topic: Control Engineering
• Status: Published
• ISBN/ISSN/Other: ISSN: 0020-0255