Quadrant scan for multi-scale transition detection

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Transition detection in temporal and nontemporal signals is a problem encountered in various disciplines. We investigate the quadrant scan technique to analyze recurrence plots to identify tipping points of a dynamical system. We define two types of transition, state-transition and dynamic-transition, and prove analytically the ability of quadrant scans to detect both types. We then provide an extension by considering a weighting scheme to overcome limitations of the standard scheme. We further highlight the merits of the quadrant scan and our extension by studying several applications. The ability of the quadrant scan and its extension to deal with nontemporal, multivariate, or large data sets as well as their capability to classify multiscale transitions are demonstrated in detail through several examples and settings.

Original languageEnglish
Article number103117
JournalChaos
Volume29
Issue number10
DOIs
Publication statusPublished - 1 Oct 2019

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Quadrant
quadrants
Dynamical systems
Recurrence Plot
Transition State
Multivariate Data
State Transition
Large Data Sets
Weighting
Dynamical system
dynamical systems
Classify
plots

Cite this

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title = "Quadrant scan for multi-scale transition detection",
abstract = "Transition detection in temporal and nontemporal signals is a problem encountered in various disciplines. We investigate the quadrant scan technique to analyze recurrence plots to identify tipping points of a dynamical system. We define two types of transition, state-transition and dynamic-transition, and prove analytically the ability of quadrant scans to detect both types. We then provide an extension by considering a weighting scheme to overcome limitations of the standard scheme. We further highlight the merits of the quadrant scan and our extension by studying several applications. The ability of the quadrant scan and its extension to deal with nontemporal, multivariate, or large data sets as well as their capability to classify multiscale transitions are demonstrated in detail through several examples and settings.",
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Quadrant scan for multi-scale transition detection. / Zaitouny, Ayham; Walker, David M.; Small, Michael.

In: Chaos, Vol. 29, No. 10, 103117, 01.10.2019.

Research output: Contribution to journalArticle

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AB - Transition detection in temporal and nontemporal signals is a problem encountered in various disciplines. We investigate the quadrant scan technique to analyze recurrence plots to identify tipping points of a dynamical system. We define two types of transition, state-transition and dynamic-transition, and prove analytically the ability of quadrant scans to detect both types. We then provide an extension by considering a weighting scheme to overcome limitations of the standard scheme. We further highlight the merits of the quadrant scan and our extension by studying several applications. The ability of the quadrant scan and its extension to deal with nontemporal, multivariate, or large data sets as well as their capability to classify multiscale transitions are demonstrated in detail through several examples and settings.

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