Recent Advances in Bridging Time Series and Complex Networks

被引：0

作者：

Li, Xiang ^{[1
]}

Liu, Xin ^{[1
]}

Tse, Chi K. ^{[2
]}

机构：

[1] Fudan Univ, Dept Elect Engn, Shanghai 200433, Peoples R China

[2] Hong Kong Polytech Univ, Elect & Informat Engn Dept, Hong Kong, Hong Kong, Peoples R China

来源：

2013 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) | 2013年

关键词：

DYNAMICS;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：2505 / 2508

页数：4

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