Notice bibliographique
- Notice
000 cam 22 3 450
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010 .. $a 9783319251158
010 .. $a 3319251155 $z 9783319251134 $z 3319251139 $z 9783319251134
035 .. $a OCoLC928384887
100 .. $a 20190130d2016 m y0engy50 ba
101 0. $a eng
102 .. $a CH
105 .. $a a z 00|y|
106 .. $a s $a z
135 .. $a drc||||||||||
181 .0 $6 01 $a i $b xxxe
181 .. $6 02 $c txt $2 rdacontent
182 .0 $6 01 $a b
182 .. $6 02 $c c $2 rdamedia
200 1. $a Controlling synchronization patterns in complex networks $b Texte électronique $e doctoral thesis accepted by the Technische Universitat Berlin, Germany $f Judith Lehnert
214 .0 $a Cham $c Springer
214 .4 $d C 2016
215 .. $a 1 ressource dématérialisée
225 |. $a Springer theses
300 .. $a Notes bibliogr.
330 .. $a This research aims to achieve a fundamental understanding of synchronization and its
interplay with the topology of complex networks. Synchronization is a ubiquitous phenomenon
observed in different contexts in physics, chemistry, biology, medicine and engineering.
Most prominently, synchronization takes place in the brain, where it is associated
with several cognitive capacities but is - in abundance - a characteristic of neurological
diseases. Besides zero-lag synchrony, group and cluster states are considered, enabling
a description and study of complex synchronization patterns within the presented theory.
Adaptive control methods are developed, which allow the control of synchronization
in scenarios where parameters drift or are unknown. These methods are, therefore,
of particular interest for experimental setups or technological applications. The
theoretical framework is demonstrated on generic models, coupled chemical oscillators
and several detailed examples of neural networks
410 .0 $0 45490033 $t Springer theses (Internet) $x 2190-5061 $d 2016
676 .. $a 003.75 $v 23
801 .3 $a US $b OCoLC $c 20190130 $h 928384887 $2 marc21
801 .0 $b N $g rda ; pn
930 .. $5 FR-759999999:45575790001001 $a ACQNUM-111697 $b 759999999 $c Document numérisé $d N
