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Cyclicality, Periodicity and the Topology of Time Series

Pawel Dlotko Orcid Logo, Wanling Qiu, Simon Rudkin Orcid Logo

arXiv

Swansea University Authors: Pawel Dlotko Orcid Logo, Wanling Qiu, Simon Rudkin Orcid Logo

Abstract

Periodic and semi periodic patterns are very common in nature. In this paper we introduce a topological toolbox aiming in detecting and quantifying periodicity. The presented technique is of a general nature and may be employed wherever there is suspected cyclic behaviour in a time series with no tr...

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Published in: arXiv
Published:
Online Access: https://arxiv.org/abs/1905.12118v1
URI: https://cronfa.swan.ac.uk/Record/cronfa51890
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Abstract: Periodic and semi periodic patterns are very common in nature. In this paper we introduce a topological toolbox aiming in detecting and quantifying periodicity. The presented technique is of a general nature and may be employed wherever there is suspected cyclic behaviour in a time series with no trend. The approach is tested on a number of real-world examples enabling us to consistently demonstrate an ability to recognise periodic behaviour where conventional techniques fail to do so. Quicker to react to changes in time series behaviour, and with a high robustness to noise, the toolbox offers a powerful way to deeper understanding of time series dynamics.
Item Description: Preprint article before certification by peer review
Keywords: Data Topology, Cyclicality, Time Series, Periodicity Detection
College: Faculty of Humanities and Social Sciences