Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/39522
Title: Fast Sampling of Evolving Systems with Periodic Trajectories
Authors: Tyukin, I. Yu.
Gorban, A. N.
Tyukina, T. A.
Al-Ameri, J. M.
Korablev, Yu. A.
First Published: 19-Jul-2016
Publisher: EDP Sciences, Cambridge University Press (CUP)
Citation: Mathematical Modelling of Natural Phenomena, 2016, 11 (4), pp. 73-88 (16)
Abstract: We propose a novel method for fast and scalable evaluation of periodic solutions of systems of ordinary differential equations for a given set of parameter values and initial conditions. The equations governing the system dynamics are supposed to be of a special class, albeit admitting nonlinear parametrization and nonlinearities. The method enables to represent a given periodic solution as sums of computable integrals and functions that are explicitly dependent on parameters of interest and initial conditions. This allows invoking parallel computational streams in order to increase speed of calculations. Performance and practical implications of the method are illustrated with examples including classical predator-prey system and models of neuronal cells.
DOI Link: 10.1051/mmnp/201611406
ISSN: 0973-5348
eISSN: 1760-6101
Links: http://www.mmnp-journal.org/articles/mmnp/abs/2016/04/mmnp2016114p73/mmnp2016114p73.html
http://hdl.handle.net/2381/39522
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2016, EDP Sciences, Cambridge University Press (CUP). Deposited with reference to the publisher’s open access archiving policy.
Description: Mathematics Subject Classification: 93B30 / 34A05 / 92B99 / 93B15
Appears in Collections:Published Articles, Dept. of Mathematics

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