Model order reduction for Linear Noise Approximation using time-scale separation
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NarmadaCDCSub2016.pdf
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584.86 KB
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Author(s)
Herath, Narmada K
Del Vecchio, Domitilla
Date Issued
December 2016
Journal
2016 IEEE 55th Conference on Decision and Control (CDC)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Herath, Narmada, and Domitilla Del Vecchio. “Model Order Reduction for Linear Noise Approximation Using Time-Scale Separation.” 2016 IEEE 55th Conference on Decision and Control (CDC) (December 2016), Las Vegas, NV, USA, Institute of Electrical and Electronics Engineers (IEEE), 2016.
Version
Author's final manuscript
Abstract
In this paper, we focus on model reduction of biomolecular systems with multiple time-scales, modeled using the Linear Noise Approximation. Considering systems where the Linear Noise Approximation can be written in singular perturbation form, with ε as the singular perturbation parameter, we obtain a reduced order model that approximates the slow variable dynamics of the original system. In particular, we show that, on a finite time-interval, the first and second moments of the reduced system are within an O(ε)-neighborhood of the first and second moments of the slow variable dynamics of the original system. The approach is illustrated on an example of a biomolecular system that exhibits time-scale separation.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Mechanical Engineering
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/CDC.2016.7799173
