HUBSYNC

Synchronization in heterogeneous Networks

 Coordinatore IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE 

 Organization address address: SOUTH KENSINGTON CAMPUS EXHIBITION ROAD
city: LONDON
postcode: SW7 2AZ

contact info
Titolo: Ms.
Nome: Brooke
Cognome: Alasya
Email: send email
Telefono: +44 207 594 1181
Fax: +44 207 594 1418

 Nazionalità Coordinatore United Kingdom [UK]
 Totale costo 209˙033 €
 EC contributo 209˙033 €
 Programma FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call FP7-PEOPLE-2011-IIF
 Funding Scheme MC-IIF
 Anno di inizio 2013
 Periodo (anno-mese-giorno) 2013-02-15   -   2015-02-14

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE

 Organization address address: SOUTH KENSINGTON CAMPUS EXHIBITION ROAD
city: LONDON
postcode: SW7 2AZ

contact info
Titolo: Ms.
Nome: Brooke
Cognome: Alasya
Email: send email
Telefono: +44 207 594 1181
Fax: +44 207 594 1418

UK (LONDON) coordinator 209˙033.40

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networks    spontaneous    network    levels    pathological    synchronization   

 Obiettivo del progetto (Objective)

'In most realistic networked systems where synchronization is relevant, strong synchronization may also be related to pathological activities such as epileptic seizures and Parkinson disease in neural networks, to extinction in ecology, and social catastrophes in epidemic spreading. Recent experiments have revealed that various levels of synchronization are needed to avoid pathological activities and enable a system to have flexibility and robustness. Despite the growing interest in network dynamics, the present state of knowledge cannot explain the various levels of synchronization observed in real-life complex systems.

A fundamental goal of this project is the development of a theory for emergence spontaneous of synchronization in heterogeneous networks of interacting dynamical systems. A core intention is to determine how the network ability to complement various levels of stable synchronization depends on the network structural parameters such as degree distribution and spectral properties of the graph. These results play a vital role towards the ultimate goal of understanding the emerging spontaneous collective motion in complex systems.'

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