Period and signal reconstruction from the curve of trains of samples

Abstract A finite sequence of equidistant samples (a sample‐train) of a periodic signal can be identified with a point in a multidimensional space. Such a point depends on the signal, the sampling period, and the starting time of the sequence. If the starting time varies, then the corresponding poin...

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Main Author: Marek W. Rupniewski
Format: Article
Language:English
Published: Wiley 2022-04-01
Series:IET Signal Processing
Subjects:
Online Access:https://doi.org/10.1049/sil2.12086
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author Marek W. Rupniewski
author_facet Marek W. Rupniewski
author_sort Marek W. Rupniewski
collection DOAJ
description Abstract A finite sequence of equidistant samples (a sample‐train) of a periodic signal can be identified with a point in a multidimensional space. Such a point depends on the signal, the sampling period, and the starting time of the sequence. If the starting time varies, then the corresponding point moves along a closed curve. We prove that this curve, that is, the set of all sample‐trains of a given length, determines the signal period, provided that the sampling period is known and is smaller than half of the signal period. The presented result is proved with the help of the theory of rotation numbers developed by Poincaré. We also prove that the curve of sample‐trains determines the signal up to a time shift, provided that the ratio of the sampling period to the period of the signal is irrational. A counterexample shows that the assumption on the incommensurability of the periods cannot be dropped. Eventually, we show how to estimate the period of a signal from a finite number of its sample‐trains.
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spelling doaj-art-38e5f028aeff4f20b6706f98c9b3f6412025-08-20T03:55:11ZengWileyIET Signal Processing1751-96751751-96832022-04-0116223223710.1049/sil2.12086Period and signal reconstruction from the curve of trains of samplesMarek W. Rupniewski0Institute of Electronic Systems Warsaw University of Technology Warsaw PolandAbstract A finite sequence of equidistant samples (a sample‐train) of a periodic signal can be identified with a point in a multidimensional space. Such a point depends on the signal, the sampling period, and the starting time of the sequence. If the starting time varies, then the corresponding point moves along a closed curve. We prove that this curve, that is, the set of all sample‐trains of a given length, determines the signal period, provided that the sampling period is known and is smaller than half of the signal period. The presented result is proved with the help of the theory of rotation numbers developed by Poincaré. We also prove that the curve of sample‐trains determines the signal up to a time shift, provided that the ratio of the sampling period to the period of the signal is irrational. A counterexample shows that the assumption on the incommensurability of the periods cannot be dropped. Eventually, we show how to estimate the period of a signal from a finite number of its sample‐trains.https://doi.org/10.1049/sil2.12086dynamical systemperiod estimationrotation numbersignal samplingtime delay embedding
spellingShingle Marek W. Rupniewski
Period and signal reconstruction from the curve of trains of samples
IET Signal Processing
dynamical system
period estimation
rotation number
signal sampling
time delay embedding
title Period and signal reconstruction from the curve of trains of samples
title_full Period and signal reconstruction from the curve of trains of samples
title_fullStr Period and signal reconstruction from the curve of trains of samples
title_full_unstemmed Period and signal reconstruction from the curve of trains of samples
title_short Period and signal reconstruction from the curve of trains of samples
title_sort period and signal reconstruction from the curve of trains of samples
topic dynamical system
period estimation
rotation number
signal sampling
time delay embedding
url https://doi.org/10.1049/sil2.12086
work_keys_str_mv AT marekwrupniewski periodandsignalreconstructionfromthecurveoftrainsofsamples