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  Quantifying uncertainty in state and parameter estimation

Parlitz, U., Schumann-Bischoff, J., & Luther, S. (2014). Quantifying uncertainty in state and parameter estimation. Physical Review E, 89(5), 050902-1-050902-5. doi:10.1103/PhysRevE.89.050902.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0029-0F41-F Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0029-0F42-D
Genre: Journal Article

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 Creators:
Parlitz, Ulrich1, Author              
Schumann-Bischoff, Jan1, Author              
Luther, Stefan1, Author              
Affiliations:
1Research Group Biomedical Physics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063288              

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Free keywords: SYSTEM IDENTIFICATION; DATA ASSIMILATION; TIME-SERIES; SYNCHRONIZATION; OBSERVABILITY
 Abstract: Observability of state variables and parameters of a dynamical system from an observed time series is analyzed and quantified by means of the Jacobian matrix of the delay coordinates map. For each state variable and each parameter to be estimated, a measure of uncertainty is introduced depending on the current state and parameter values, which allows us to identify regions in state and parameter space where the specific unknown quantity can(not) be estimated from a given time series. The method is demonstrated using the Ikeda map and the Hindmarsh-Rose model.

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Language(s): eng - English
 Dates: 2014-05-15
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: eDoc: 708930
DOI: 10.1103/PhysRevE.89.050902
 Degree: -

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Title: Physical Review E
  Alternative Title : Phys. Rev. E
Source Genre: Journal
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Publ. Info: -
Pages: - Volume / Issue: 89 (5) Sequence Number: - Start / End Page: 050902-1 - 050902-5 Identifier: ISSN: 1539-3755