東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Patterns of synchrony in complex net...

Berner, Rico.

Linked to FindBook

Google Book

Amazon

博客來

Patterns of synchrony in complex networks of adaptively coupled oscillators

Record Type:	Electronic resources : Monograph/item
Title/Author:	Patterns of synchrony in complex networks of adaptively coupled oscillators/ by Rico Berner.
Author:	Berner, Rico.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xvi, 203 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Fundamentals of Adaptive and Complex Dynamical Networks -- Population of Hodgkin-Huxley Neurons With Spike Timing-Dependent Plasticity -- One-cluster States in Adaptive Networks of Coupled Phase Oscillators-. Multicluster States in Adaptive Networks of Coupled Phase Oscillators.
Contained By:	Springer Nature eBook
Subject:	Synchronization. -
Online resource:	https://doi.org/10.1007/978-3-030-74938-5
ISBN:	9783030749385

Patterns of synchrony in complex networks of adaptively coupled oscillators
Berner, Rico.

Patterns of synchrony in complex networks of adaptively coupled oscillators[electronic resource] /by Rico Berner. - Cham :Springer International Publishing :2021. - xvi, 203 p. :ill., digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

Introduction -- Fundamentals of Adaptive and Complex Dynamical Networks -- Population of Hodgkin-Huxley Neurons With Spike Timing-Dependent Plasticity -- One-cluster States in Adaptive Networks of Coupled Phase Oscillators-. Multicluster States in Adaptive Networks of Coupled Phase Oscillators.

The focus of this thesis is the interplay of synchrony and adaptivity in complex networks. Synchronization is a ubiquitous phenomenon observed in different contexts in physics, chemistry, biology, neuroscience, medicine, socioeconomic systems, and engineering. Most prominently, synchronization takes place in the brain, where it is associated with cognitive capacities like learning and memory, but is also a characteristic of neurological diseases like Parkinson and epilepsy. Adaptivity is common in many networks in nature and technology, where the connectivity changes in time, i.e., the strength of the coupling is continuously adjusted depending upon the dynamic state of the system, for instance synaptic neuronal plasticity in the brain. This research contributes to a fundamental understanding of various synchronization patterns, including hierarchical multifrequency clusters, chimeras and other partial synchronization states. After a concise survey of the fundamentals of adaptive and complex dynamical networks and synaptic plasticity, in the first part of the thesis the existence and stability of cluster synchronization in globally coupled adaptive networks is discussed for simple paradigmatic phase oscillators as well as for a more realistic neuronal oscillator model with spike-timing dependent plasticity. In the second part of the thesis the interplay of adaptivity and connectivity is investigated for more complex network structures like nonlocally coupled rings, random networks, and multilayer systems. Besides presenting a plethora of novel, sometimes intriguing patterns of synchrony, the thesis makes a number of pioneering methodological advances, where rigorous mathematical proofs are given in the Appendices. These results are of interest not only from a fundamental point of view, but also with respect to challenging applications in neuroscience and technological systems.

ISBN: 9783030749385

Standard No.: 10.1007/978-3-030-74938-5doiSubjects--Topical Terms:

578767
Synchronization.

LC Class. No.: Q172.5.S96 / B47 2021

Dewey Class. No.: 003.72

Patterns of synchrony in complex networks of adaptively coupled oscillators
LDR:03276nmm a2200349 a 4500 001 2240968
003 DE-He213
005 20210531164801.0
006 m d
007 cr nn 008maaau
008 211111s2021 sz s 0 eng d
020 $a 9783030749385 $q (electronic bk.)
020 $a 9783030749378 $q (paper)
024 7 $a 10.1007/978-3-030-74938-5 $2 doi
035 $a 978-3-030-74938-5
040 $a GP $c GP
041 0 $a eng
050 4 $a Q172.5.S96 $b B47 2021
072 7 $a PHS $2 bicssc
072 7 $a SCI055000 $2 bisacsh
072 7 $a PHS $2 thema
072 7 $a PHDT $2 thema
082 0 4 $a 003.72 $2 23
090 $a Q172.5.S96 $b B525 2021
100 1 $a Berner, Rico. $3 3496374
245 1 0 $a Patterns of synchrony in complex networks of adaptively coupled oscillators $h [electronic resource] / $c by Rico Berner.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xvi, 203 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer theses, $x 2190-5053
505 0 $a Introduction -- Fundamentals of Adaptive and Complex Dynamical Networks -- Population of Hodgkin-Huxley Neurons With Spike Timing-Dependent Plasticity -- One-cluster States in Adaptive Networks of Coupled Phase Oscillators-. Multicluster States in Adaptive Networks of Coupled Phase Oscillators.
520 $a The focus of this thesis is the interplay of synchrony and adaptivity in complex networks. Synchronization is a ubiquitous phenomenon observed in different contexts in physics, chemistry, biology, neuroscience, medicine, socioeconomic systems, and engineering. Most prominently, synchronization takes place in the brain, where it is associated with cognitive capacities like learning and memory, but is also a characteristic of neurological diseases like Parkinson and epilepsy. Adaptivity is common in many networks in nature and technology, where the connectivity changes in time, i.e., the strength of the coupling is continuously adjusted depending upon the dynamic state of the system, for instance synaptic neuronal plasticity in the brain. This research contributes to a fundamental understanding of various synchronization patterns, including hierarchical multifrequency clusters, chimeras and other partial synchronization states. After a concise survey of the fundamentals of adaptive and complex dynamical networks and synaptic plasticity, in the first part of the thesis the existence and stability of cluster synchronization in globally coupled adaptive networks is discussed for simple paradigmatic phase oscillators as well as for a more realistic neuronal oscillator model with spike-timing dependent plasticity. In the second part of the thesis the interplay of adaptivity and connectivity is investigated for more complex network structures like nonlocally coupled rings, random networks, and multilayer systems. Besides presenting a plethora of novel, sometimes intriguing patterns of synchrony, the thesis makes a number of pioneering methodological advances, where rigorous mathematical proofs are given in the Appendices. These results are of interest not only from a fundamental point of view, but also with respect to challenging applications in neuroscience and technological systems.
650 0 $a Synchronization. $3 578767
650 0 $a Dynamics. $3 519830
650 1 4 $a Complex Systems. $3 1566441
650 2 4 $a Mathematical Models of Cognitive Processes and Neural Networks. $3 1619875
650 2 4 $a Dynamical Systems and Ergodic Theory. $3 891276
650 2 4 $a Vibration, Dynamical Systems, Control. $3 893843
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Springer theses. $3 1314442
856 4 0 $u https://doi.org/10.1007/978-3-030-74938-5
950 $a Physics and Astronomy (SpringerNature-11651)