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Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Nov;84(5 Pt 2):056214. Epub 2011 Nov 23.

State and parameter estimation using unconstrained optimization.

Author information

1
Drittes Physikalisches Institut, Georg-August-Universität Göttingen, Göttingen, Germany.

Abstract

We present an efficient method for estimating variables and parameters of a given system of ordinary differential equations by adapting the model output to an observed time series from the (physical) process described by the model. The proposed method is based on (unconstrained) nonlinear optimization exploiting the particular structure of the relevant cost function. To illustrate the features and performance of the method, simulations are presented using chaotic time series generated by the Colpitts oscillator, the three-dimensional Hindmarsh-Rose neuron model, and a nine-dimensional extended Rössler system.

PMID:
22181491
DOI:
10.1103/PhysRevE.84.056214
[Indexed for MEDLINE]

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