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Optimizing coupled oscillators for stability

Optimizing coupled oscillators for stability
Optimizing coupled oscillators for stability
Synchronization in chaotic oscillatory systems has a wide array of applications in biology, physics and communication systems. Over the past 10 years there has been considerable interest in the synchronization properties of small-world and scale-free networks. In this paper, we define the fitness of a configuration of coupled oscillators as its ability to synchronize. We then employ an optimization algorithm to determine network structures that lead to an enhanced ability to synchronize. The optimized networks generally have low clustering, small diameters, short path-length, are disassortative, and have a high degree of homogeneity in their degree and load distributions.
3-540-30462-2
1327-1330
Newth, David
e4f6e8f6-b8cf-49c0-b3db-489c50143a8a
Brede, Markus
bbd03865-8e0b-4372-b9d7-cd549631f3f7
Newth, David
e4f6e8f6-b8cf-49c0-b3db-489c50143a8a
Brede, Markus
bbd03865-8e0b-4372-b9d7-cd549631f3f7

Newth, David and Brede, Markus (2005) Optimizing coupled oscillators for stability. 18th Australian Joint Conference on Artificial Intelligence, Australia. 05 - 09 Dec 2005. pp. 1327-1330 .

Record type: Conference or Workshop Item (Paper)

Abstract

Synchronization in chaotic oscillatory systems has a wide array of applications in biology, physics and communication systems. Over the past 10 years there has been considerable interest in the synchronization properties of small-world and scale-free networks. In this paper, we define the fitness of a configuration of coupled oscillators as its ability to synchronize. We then employ an optimization algorithm to determine network structures that lead to an enhanced ability to synchronize. The optimized networks generally have low clustering, small diameters, short path-length, are disassortative, and have a high degree of homogeneity in their degree and load distributions.

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More information

Published date: 2005
Venue - Dates: 18th Australian Joint Conference on Artificial Intelligence, Australia, 2005-12-05 - 2005-12-09
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 272889
URI: http://eprints.soton.ac.uk/id/eprint/272889
ISBN: 3-540-30462-2
PURE UUID: afba40e6-2025-467c-ae05-2ea273da6293

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Date deposited: 29 Sep 2011 16:25
Last modified: 16 Jul 2019 22:12

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Contributors

Author: David Newth
Author: Markus Brede

University divisions

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