A distribution input–output polynomial approach for estimating parameters in nonlinear models. Application to a chikungunya model-Reference-Cited by-同舟云学术

A distribution input–output polynomial approach for estimating parameters in nonlinear models. Application to a chikungunya model

Published:2018-03 Issue: Volume:331 Page:104-118
ISSN:0377-0427
Container-title:Journal of Computational and Applied Mathematics
language:en
Short-container-title:Journal of Computational and Applied Mathematics

Author:

Verdière N.^ORCID,Zhu S.,Denis-Vidal L.

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Mathematics

Reference22 articles.

1. Optimization Techniques: An Overview;Kiranyaz,2014

2. Identification of Parametric Models from Experimental Data;Walter,1997

3. An algorithm for converting nonlinear differential equations to integral equations with an application to parameter estimation from noisy data;Boulier,2014

4. L. Denis-Vidal, G. Joly-Blanchard, N. Verdière, Identifiability and estimation of nonlinear models: A distribution framework, in: Proc. ECC 2007, Kos, Grèce, 2–5 juillet, 2007.

5. More about process identification;Loeb;Automatica,1965

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