| Full text | |
| Author(s): |
Stankovski, Tomislav
[1, 2]
;
Pereira, Tiago
[3, 4]
;
McClintock, Peter V. E.
[1]
;
Stefanovska, Aneta
[1]
Total Authors: 4
|
| Affiliation: | [1] Univ Lancaster, Dept Phys, Lancaster LA1 4YB - England
[2] Ss Cyril & Methodius Univ, Fac Med, 50 Divizija 6, Skopje 1000 - Macedonia
[3] Univ Sao Paulo, Inst Math & Comp Sci, BR-13566590 Sao Carlos, SP - Brazil
[4] Imperial Coll London, Dept Math, London SW7 2AZ - England
Total Affiliations: 4
|
| Document type: | Journal article |
| Source: | REVIEWS OF MODERN PHYSICS; v. 89, n. 4 NOV 6 2017. |
| Web of Science Citations: | 56 |
| Abstract | |
The dynamical systems found in nature are rarely isolated. Instead they interact and influence each other. The coupling functions that connect them contain detailed information about the functional mechanisms underlying the interactions and prescribe the physical rule specifying how an interaction occurs. A coherent and comprehensive review is presented encompassing the rapid progress made recently in the analysis, understanding, and applications of coupling functions. The basic concepts and characteristics of coupling functions are presented through demonstrative examples of different domains, revealing the mechanisms and emphasizing their multivariate nature. The theory of coupling functions is discussed through gradually increasing complexity from strong and weak interactions to globally coupled systems and networks. A variety of methods that have been developed for the detection and reconstruction of coupling functions from measured data is described. These methods are based on different statistical techniques for dynamical inference. Stemming from physics, such methods are being applied in diverse areas of science and technology, including chemistry, biology, physiology, neuroscience, social sciences, mechanics, and secure communications. This breadth of application illustrates the universality of coupling functions for studying the interaction mechanisms of coupled dynamical systems. (AU) | |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |