FitzHughNagumo()

Unscented Kalman Filter (UKF) applied to FitzHugh-Nagumo neuron dynamics.
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Updated 30 Aug 2016

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Unscented Kalman Filter (UKF) applied to FitzHugh-Nagumo neuron dynamics.

The neuronal transmembrane voltage is assumed to be observed, hidden ion currents and input signals to the model neuron are estimated from the observed voltage.

Due to it's modular structure, applications to similar problems should be easy to accomplish.
FitzHughNagumo() is the main program and calls the other programs.

A detailed description is provided in
H.U. Voss, J. Timmer & J. Kurths, Nonlinear dynamical system identification from uncertain and indirect measurements, Int. J. Bifurcation and Chaos 14, 1905-1933 (2004).
I will be happy to email this paper on request. It contains a tutorial about the estimation of hidden states and unscented Kalman filtering.
For commercial use and questions, please contact me.

Henning U. Voss, Ph.D.
Associate Professor of Physics in Radiology
Citigroup Biomedical Imaging Center
Weill Medical College of Cornell University
516 E 72nd Street
New York, NY 10021
Tel. 001-212 746-5216, Fax. 001-212 746-6681
Email: hev2006@med.cornell.edu

Cite As

Henning U. Voss (2024). FitzHughNagumo() (https://www.mathworks.com/matlabcentral/fileexchange/37355-fitzhughnagumo), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R12
Compatible with any release
Platform Compatibility
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Version Published Release Notes
1.5.0.0

Written 15. 7. 2002
Updated 30. 8. 2016 (R2015b):
- Change of random number generator to ensure future compatibility
- Eliminiation of yellow warnings

1.4.0.0

Improved documentation, code unchanged, modified license

1.3.0.0

I combined all files into one to make download easier

1.0.0.0