Hybrid Cubature Kalman filtering for identifying nonlinear models from sampled recording: Estimation of neuronal dynamics

Kalman filtering methods have long been regarded as efficient adaptive Bayesian techniques for estimating hidden states in models of linear dynamical systems under Gaussian uncertainty. Recent advents of the Cubature Kalman filter (CKF) have extended this efficient estimation property to nonlinear s...

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Detalles Bibliográficos
Autores principales: Madi, Mahmoud K., Karameh, Fadi N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5519212/
https://www.ncbi.nlm.nih.gov/pubmed/28727850
http://dx.doi.org/10.1371/journal.pone.0181513

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5519212/
https://www.ncbi.nlm.nih.gov/pubmed/28727850
http://dx.doi.org/10.1371/journal.pone.0181513

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