國立虎尾科技大學 |

Controlling Synchronization Patterns in Complex Networks

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Controlling Synchronization Patterns in Complex Networks/ by Judith Lehnert.
作者:	Lehnert, Judith.
面頁冊數:	XV, 203 p.online resource. :
Contained By:	Springer Nature eBook
標題:	Physics. -
電子資源:	https://doi.org/10.1007/978-3-319-25115-8
ISBN:	9783319251158

Controlling Synchronization Patterns in Complex Networks
Lehnert, Judith.

Controlling Synchronization Patterns in Complex Networks[electronic resource] /by Judith Lehnert. - 1st ed. 2016. - XV, 203 p.online resource. - Springer Theses, Recognizing Outstanding Ph.D. Research,2190-5053. - Springer Theses, Recognizing Outstanding Ph.D. Research,.

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

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

564049
Physics.

LC Class. No.: QC1-999

Dewey Class. No.: 621

Controlling Synchronization Patterns in Complex Networks
LDR:02856nam a22004215i 4500 001 975196
003 DE-He213
005 20200706021231.0
007 cr nn 008mamaa
008 201211s2016 gw | s |||| 0|eng d
020 $a 9783319251158 $9 978-3-319-25115-8
024 7 $a 10.1007/978-3-319-25115-8 $2 doi
035 $a 978-3-319-25115-8
050 4 $a QC1-999
072 7 $a PHU $2 bicssc
072 7 $a SCI064000 $2 bisacsh
072 7 $a PHU $2 thema
072 7 $a PBKD $2 thema
082 0 4 $a 621 $2 23
100 1 $a Lehnert, Judith. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1103414
245 1 0 $a Controlling Synchronization Patterns in Complex Networks $h [electronic resource] / $c by Judith Lehnert.
250 $a 1st ed. 2016.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a XV, 203 p. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Springer Theses, Recognizing Outstanding Ph.D. Research, $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 Physics. $3 564049
650 0 $a Neural networks (Computer science) . $3 1253765
650 0 $a Physical chemistry. $3 1148725
650 0 $a Vibration. $3 595749
650 0 $a Dynamical systems. $3 1249739
650 0 $a Dynamics. $3 592238
650 0 $a System theory. $3 566168
650 1 4 $a Applications of Graph Theory and Complex Networks. $3 1113468
650 2 4 $a Mathematical Models of Cognitive Processes and Neural Networks. $3 884110
650 2 4 $a Physical Chemistry. $3 668972
650 2 4 $a Vibration, Dynamical Systems, Control. $3 670825
650 2 4 $a Systems Theory, Control. $3 669337
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319251134
776 0 8 $i Printed edition: $z 9783319251141
776 0 8 $i Printed edition: $z 9783319370903
830 0 $a Springer Theses, Recognizing Outstanding Ph.D. Research, $x 2190-5053 $3 1253569
856 4 0 $u https://doi.org/10.1007/978-3-319-25115-8
912 $a ZDB-2-PHA
912 $a ZDB-2-SXP
950 $a Physics and Astronomy (SpringerNature-11651)
950 $a Physics and Astronomy (R0) (SpringerNature-43715)