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Estimation of biophysical parameters in a neuron model under random fluctuations.

Authors :
Upadhyay, Ranjit Kumar
Paul, Chinmoy
Mondal, Argha
Vishwakarma, Gajendra K.
Source :
Applied Mathematics & Computation. Jul2018, Vol. 329, p364-373. 10p.
Publication Year :
2018

Abstract

In this paper, an attempt has been made to estimate the biophysical parameters in an improved version of Morris–Lecar (M–L) neuron model in a noisy environment. To observe the influence of noisy stimulation in estimation procedure, a Gaussian white noise has been added to the membrane voltage of the model system. Estimation of the parameters has been investigated by a proposed algorithm. The denoising technique (local projection method) has been applied to reduce the influence of noisy stimuli and the effectiveness of the method is reported. The proposed scheme performs well for an excitable neuron model and provides good estimates between the estimated parameters and the actual values in a reasonable way. This approach can be used for parameter estimation for other nonlinear dynamical systems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00963003
Volume :
329
Database :
Academic Search Index
Journal :
Applied Mathematics & Computation
Publication Type :
Academic Journal
Accession number :
128416181
Full Text :
https://doi.org/10.1016/j.amc.2018.02.011