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: | 9783319251134 |
| Publication date: | 17th November 2015 |
| Author: | Judith Lehnert |
| Publisher: | Springer an imprint of Springer International Publishing |
| Format: | Hardback |
| Pagination: | 203 pages |
| Series: | Springer Theses |
| Genres: |
Combinatorics and graph theory Mathematical modelling Cybernetics and systems theory Engineering: Mechanics of solids Physical chemistry |
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.
Controlling Synchronization Patterns in Complex Networks features in the following genres: Combinatorics and graph theory, Mathematical modelling, Cybernetics and systems theory, Engineering: Mechanics of solids, Physical chemistry
Controlling Synchronization Patterns in Complex Networks is available in Hardback
Controlling Synchronization Patterns in Complex Networks was written by Judith Lehnert and published by Springer an imprint of Springer International Publishing
Controlling Synchronization Patterns in Complex Networks has 203 pages
Yes it is part of Springer Theses series