Ordinal Network Measures - Quantifying Determinism in Data

Michael Small; Michael McCullough; Konstantinos Sakellariou

doi:10.1109/ISCAS.2018.8351743

Ordinal Network Measures - Quantifying Determinism in Data

Michael Small, Michael McCullough, Konstantinos Sakellariou

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

8 Citations (Web of Science)

Abstract

The ordinal network construction method was proposed at ISCAS2013. Since then a great deal of theoretical and experimental work has developed these methods to the point where they can be applied as a diagnostic tool to understand changing system behaviour from observed time series. We now also have a solid theoretical understanding of what these methods measure and why this is useful. This talk will review the method and demonstrate its application to computation and experimental systems with the aim of detecting changes or bifurcations in the underlying system. We will conclude with applications to biosignal processing for cardiac interbeat interval time series and electroencephalograms.

Original language	English
Title of host publication	2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Volume	2018-May
ISBN (Electronic)	9781538648810
DOIs	https://doi.org/10.1109/ISCAS.2018.8351743
Publication status	Published - 26 Apr 2018
Event	2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Firenze Fiera Congress and Exhibition Center, Florence, Italy Duration: 27 May 2018 → 30 May 2018

Conference

Conference	2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018
Country/Territory	Italy
City	Florence
Period	27/05/18 → 30/05/18

Access to Document

10.1109/ISCAS.2018.8351743

Cite this

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title = "Ordinal Network Measures - Quantifying Determinism in Data",

abstract = "The ordinal network construction method was proposed at ISCAS2013. Since then a great deal of theoretical and experimental work has developed these methods to the point where they can be applied as a diagnostic tool to understand changing system behaviour from observed time series. We now also have a solid theoretical understanding of what these methods measure and why this is useful. This talk will review the method and demonstrate its application to computation and experimental systems with the aim of detecting changes or bifurcations in the underlying system. We will conclude with applications to biosignal processing for cardiac interbeat interval time series and electroencephalograms.",

keywords = "chaos, complex network, nonlinear time series, ordinal network",

author = "Michael Small and Michael McCullough and Konstantinos Sakellariou",

year = "2018",

month = apr,

day = "26",

doi = "10.1109/ISCAS.2018.8351743",

language = "English",

volume = "2018-May",

booktitle = "2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

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note = "2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 ; Conference date: 27-05-2018 Through 30-05-2018",

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Small, M, McCullough, M & Sakellariou, K 2018, Ordinal Network Measures - Quantifying Determinism in Data. in 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings. vol. 2018-May, 8351743, IEEE, Institute of Electrical and Electronics Engineers, 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018, Florence, Italy, 27/05/18. https://doi.org/10.1109/ISCAS.2018.8351743

Ordinal Network Measures - Quantifying Determinism in Data. / Small, Michael; McCullough, Michael; Sakellariou, Konstantinos.

2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings. Vol. 2018-May IEEE, Institute of Electrical and Electronics Engineers, 2018. 8351743.

Research output: Chapter in Book/Conference paper › Conference paper › peer-review

TY - GEN

T1 - Ordinal Network Measures - Quantifying Determinism in Data

AU - Small, Michael

AU - McCullough, Michael

AU - Sakellariou, Konstantinos

PY - 2018/4/26

Y1 - 2018/4/26

N2 - The ordinal network construction method was proposed at ISCAS2013. Since then a great deal of theoretical and experimental work has developed these methods to the point where they can be applied as a diagnostic tool to understand changing system behaviour from observed time series. We now also have a solid theoretical understanding of what these methods measure and why this is useful. This talk will review the method and demonstrate its application to computation and experimental systems with the aim of detecting changes or bifurcations in the underlying system. We will conclude with applications to biosignal processing for cardiac interbeat interval time series and electroencephalograms.

AB - The ordinal network construction method was proposed at ISCAS2013. Since then a great deal of theoretical and experimental work has developed these methods to the point where they can be applied as a diagnostic tool to understand changing system behaviour from observed time series. We now also have a solid theoretical understanding of what these methods measure and why this is useful. This talk will review the method and demonstrate its application to computation and experimental systems with the aim of detecting changes or bifurcations in the underlying system. We will conclude with applications to biosignal processing for cardiac interbeat interval time series and electroencephalograms.

KW - chaos

KW - complex network

KW - nonlinear time series

KW - ordinal network

UR - http://www.scopus.com/inward/record.url?scp=85057094237&partnerID=8YFLogxK

U2 - 10.1109/ISCAS.2018.8351743

DO - 10.1109/ISCAS.2018.8351743

M3 - Conference paper

AN - SCOPUS:85057094237

VL - 2018-May

BT - 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - 2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018

Y2 - 27 May 2018 through 30 May 2018

ER -

Ordinal Network Measures - Quantifying Determinism in Data

Abstract

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Quantifying complexity and measuring structure within complex systems

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Ordinal Network Measures - Quantifying Determinism in Data

Abstract

Conference

Access to Document

Other files and links

Fingerprint

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Quantifying complexity and measuring structure within complex systems

Cite this