國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Controlling synchronization patterns...

Lehnert, Judith.

Controlling synchronization patterns in complex networks

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Controlling synchronization patterns in complex networksby Judith Lehnert.
作者:	Lehnert, Judith.
出版者:	Cham :Springer International Publishing :2016.
面頁冊數:	xv, 203 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Synchronization.
電子資源:	http://dx.doi.org/10.1007/978-3-319-25115-8
ISBN:	9783319251158$q(electronic bk.)

Controlling synchronization patterns in complex networks
Lehnert, Judith.

Controlling synchronization patterns in complex networks[electronic resource] /by Judith Lehnert. - Cham :Springer International Publishing :2016. - xv, 203 p. :ill., digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

Introduction -- Complex Dynamical Networks -- Synchronization In Complex Networks -- Control of Synchronization Transitions by Balancing Excitatory and Inhibitory Coupling -- Cluster and Group Synchrony: The Theory -- Zero-Lag and Cluster Synchrony: Towards Applications -- Adaptive Control -- Adaptive Time-Delayed Feedback Control -- Adaptive Control of Cluster States in Network Motifs -- Adaptive Topologies -- Conclusion.

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.

ISBN: 9783319251158$q(electronic bk.)

Standard No.: 10.1007/978-3-319-25115-8doiSubjects--Topical Terms:

226631
Synchronization.

LC Class. No.: Q172.5.S96

Dewey Class. No.: 003.75

Controlling synchronization patterns in complex networks
LDR:02434nmm a2200337 a 4500 001 482001
003 DE-He213
005 20160801163531.0
006 m d
007 cr nn 008maaau
008 161007s2016 gw s 0 eng d
020 $a 9783319251158$q(electronic bk.)
020 $a 9783319251134$q(paper)
024 7 $a 10.1007/978-3-319-25115-8 $2 doi
035 $a 978-3-319-25115-8
040 $a GP $c GP
041 0 $a eng
050 4 $a Q172.5.S96
072 7 $a PHU $2 bicssc
072 7 $a PBKD $2 bicssc
072 7 $a SCI064000 $2 bisacsh
082 0 4 $a 003.75 $2 23
090 $a Q172.5.S96 $b L523 2016
100 1 $a Lehnert, Judith. $3 738411
245 1 0 $a Controlling synchronization patterns in complex networks $h [electronic resource] / $c by Judith Lehnert.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a xv, 203 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer theses, $x 2190-5053
505 0 $a Introduction -- Complex Dynamical Networks -- Synchronization In Complex Networks -- Control of Synchronization Transitions by Balancing Excitatory and Inhibitory Coupling -- Cluster and Group Synchrony: The Theory -- Zero-Lag and Cluster Synchrony: Towards Applications -- Adaptive Control -- Adaptive Time-Delayed Feedback Control -- Adaptive Control of Cluster States in Network Motifs -- Adaptive Topologies -- Conclusion.
520 $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.
650 0 $a Synchronization. $3 226631
650 0 $a Automatic control. $3 182078
650 1 4 $a Physics. $3 179414
650 2 4 $a Complex Networks. $3 489352
650 2 4 $a Mathematical Models of Cognitive Processes and Neural Networks. $3 567118
650 2 4 $a Physical Chemistry. $3 273698
650 2 4 $a Vibration, Dynamical Systems, Control. $3 274667
650 2 4 $a Systems Theory, Control. $3 274654
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Springer theses. $3 557607
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-25115-8
950 $a Physics and Astronomy (Springer-11651)