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On a variable step size modification of Hines' method in computational  neuroscience
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.).
(English)Manuscript (preprint) (Other academic)
Abstract [en]

  For simulating large networks of neurons Hines proposed a method which usesextensively the structure of the arising systems of ordinary differentialequations in order to obtain an efficient implementation. The original methodrequires constant step sizes and produces the solution on a staggered grid. Inthe present paper a one-step modification of this method is introduced andanalyzed with respect to their stability properties. The new method allows forstep size control. Local error estimators are constructed. The method has beenimplemented in matlab and tested using simple Hodgkin-Huxley type models.Comparisons with standard state-of-the-art solvers are provided.

National Category
Computational Mathematics
Research subject
Applied and Computational Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-218773OAI: oai:DiVA.org:kth-218773DiVA: diva2:1161494
Note

QC 20171211

Available from: 2017-11-30 Created: 2017-11-30 Last updated: 2017-12-11Bibliographically approved

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Other links

http://arxiv.org/abs/1702.05917

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Hanke, Michael
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