Data assimilation methods for neuronal state and parameter estimation
type: Item
instance of: scholarly article
title: Data assimilation methods for neuronal state and parameter estimation
zbMATH Open document ID: 1405.92050
author: Matthew J. Moye
author: Casey O. Diekman
published in: The Journal of Mathematical Neuroscience
publication date: 2019-01-16T00:00:00Z
Mathematics Subject Classification ID: 92C20
zbMATH DE Number: 7002603
zbMATH Keywords: data assimilation
zbMATH Keywords: neuronal excitability
zbMATH Keywords: conductance-based models
zbMATH Keywords: parameter estimation
describes a project that uses: Neurofitter
describes a project that uses: L-BFGS
describes a project that uses: Matlab
describes a project that uses: ADiGator
describes a project that uses: OPTI
describes a project that uses: L-BFGS-B
describes a project that uses: EnKF
describes a project that uses: LBFGS-B
describes a project that uses: L-BFGS-B-C
describes a project that uses: GitHub
MaRDI profile type: Publication
full work available at URL: s13408-018-0066-8
OpenAlex ID: W2886172288
Wikidata QID: Q57104059
cites work: Q5134799
cites work: Data Assimilation
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DOI: 10.1186/S13408-018-0066-8
description: scientific article; zbMATH DE number 7002603