Literature DB >> 25353733

Quantifying uncertainty in state and parameter estimation.

Ulrich Parlitz1, Jan Schumann-Bischoff1, Stefan Luther1.   

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.

Mesh:

Year:  2014        PMID: 25353733     DOI: 10.1103/PhysRevE.89.050902

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  1 in total

1.  Estimation of neuron parameters from imperfect observations.

Authors:  Joseph D Taylor; Samuel Winnall; Alain Nogaret
Journal:  PLoS Comput Biol       Date:  2020-07-16       Impact factor: 4.475

  1 in total

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