Recent advances in bridging time series and complex networks

Xiang Li; Xin Liu; Chi Kong Tse

doi:10.1109/ISCAS.2013.6572388

Recent advances in bridging time series and complex networks

Xiang Li, Xin Liu, Chi Kong Tse

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

7 Citations (Scopus)

Abstract

This paper reviews the recent advances in bridging time series analysis and complex network theory. We first introduce the main representative approaches of mapping time series into complex networks with their potential and advantages in applications in a variety of fields, and also report the latest methods to feature complex networks with typical time series after multi-scaling transformation, and to estimate and identify the uncertain connectivity of a complex network. As an example, we show an amplitude-temporal method to fast detect arrhythmia with the indicator of the average degree of associated networks.

Original language	English
Title of host publication	2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013
Pages	2505-2508
Number of pages	4
DOIs	https://doi.org/10.1109/ISCAS.2013.6572388
Publication status	Published - 9 Sept 2013
Event	2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013 - Beijing, China Duration: 19 May 2013 → 23 May 2013

Conference

Conference	2013 IEEE International Symposium on Circuits and Systems, ISCAS 2013
Country/Territory	China
City	Beijing
Period	19/05/13 → 23/05/13

ASJC Scopus subject areas

Electrical and Electronic Engineering

More information

10.1109/ISCAS.2013.6572388

Cite this

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abstract = "This paper reviews the recent advances in bridging time series analysis and complex network theory. We first introduce the main representative approaches of mapping time series into complex networks with their potential and advantages in applications in a variety of fields, and also report the latest methods to feature complex networks with typical time series after multi-scaling transformation, and to estimate and identify the uncertain connectivity of a complex network. As an example, we show an amplitude-temporal method to fast detect arrhythmia with the indicator of the average degree of associated networks.",

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AB - This paper reviews the recent advances in bridging time series analysis and complex network theory. We first introduce the main representative approaches of mapping time series into complex networks with their potential and advantages in applications in a variety of fields, and also report the latest methods to feature complex networks with typical time series after multi-scaling transformation, and to estimate and identify the uncertain connectivity of a complex network. As an example, we show an amplitude-temporal method to fast detect arrhythmia with the indicator of the average degree of associated networks.

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M3 - Conference article published in proceeding or book

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Recent advances in bridging time series and complex networks

Abstract

Conference

ASJC Scopus subject areas

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