TY - JOUR
T1 - Evolving dynamical networks
AU - Belykh, Igor
AU - Di Bernardo, Mario
AU - Kurths, Jürgen
AU - Porfiri, Maurizio
N1 - Funding Information:
We are grateful to Tim Sauer and Joceline Lega, the Overseeing Special Issue Editors, for their patience and assistance in preparing this special issue. We would also like to thank the authors and reviewers for their truly exceptional contributions. This work was supported by the National Science Foundation under Grant Nos. DMS-1009744 (to I.B.) and CMMI-0745753 (to M.P.) and by the European Union’s Seventh Framework Programme (FP7 ICT 2011 Call 9) under grant agreement No. FP7-ICT-600610 (AlterEgo) (to M.d.B.) and the ECs Marie Curie ITN program ((FP7-PEOPLE-2011-ITN) (LINC project No. 289447) (to J.K.)).
PY - 2014
Y1 - 2014
N2 - Networks of dynamical systems are common models for many problems in physics, engineering, chemistry, biology, and social sciences. In particular, the interplay between network structure and synchronization has been extensively studied, as synchronization has been shown to play an important role in the function or dysfunction of a wide spectrum of technological and biological networks. This highly interdisciplinary special issue integrates new research contributions from different areas in applied mathematics, physics, neuroscience, and engineering, including stability and bifurcation theory, information and ergodic theory, averaging methods, and mathematical control theory. It can be roughly divided into three themes. They demonstrate that such variations can lead to the emergence of macroscopic chaos, multi-stability, and final-state uncertainty in the collective behavior of the neuronal network. Analytical techniques are used to identify the asymptotic behavior of the macroscopic mean field dynamics of the network.
AB - Networks of dynamical systems are common models for many problems in physics, engineering, chemistry, biology, and social sciences. In particular, the interplay between network structure and synchronization has been extensively studied, as synchronization has been shown to play an important role in the function or dysfunction of a wide spectrum of technological and biological networks. This highly interdisciplinary special issue integrates new research contributions from different areas in applied mathematics, physics, neuroscience, and engineering, including stability and bifurcation theory, information and ergodic theory, averaging methods, and mathematical control theory. It can be roughly divided into three themes. They demonstrate that such variations can lead to the emergence of macroscopic chaos, multi-stability, and final-state uncertainty in the collective behavior of the neuronal network. Analytical techniques are used to identify the asymptotic behavior of the macroscopic mean field dynamics of the network.
UR - http://www.scopus.com/inward/record.url?scp=84890999061&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84890999061&partnerID=8YFLogxK
U2 - 10.1016/j.physd.2013.10.008
DO - 10.1016/j.physd.2013.10.008
M3 - Editorial
AN - SCOPUS:84890999061
SN - 0167-2789
VL - 267
SP - 1
EP - 6
JO - Physica D: Nonlinear Phenomena
JF - Physica D: Nonlinear Phenomena
ER -