A Fully Automated Periodicity Detection in Time Series

Autor:	Matthieu Boussard, Tom Puech, Anthony D’Amato, Gaëtan Millerand
Rok vydání:	2020
Předmět:	symbols.namesake Fourier transform Series (mathematics) Fully automated Computer science Autocorrelation symbols State (computer science) Cluster analysis Algorithm Signal
Zdroj:	Advanced Analytics and Learning on Temporal Data ISBN: 9783030390976 AALTD@PKDD/ECML
Popis:	This paper presents a method to autonomously find periodicities in a signal. It is based on the same idea of using Fourier Transform and autocorrelation function presented in [12]. While showing interesting results this method does not perform well on noisy signals or signals with multiple periodicities. Thus, our method adds several new extra steps (hints clustering, filtering and detrending) to fix these issues. Experimental results show that the proposed method outperforms state of the art algorithms.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::efe1cb0bc2126fcb92d09d1236fd1ad5 https://doi.org/10.1007/978-3-030-39098-3_4 Zobrazit plný text záznamu