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Estimation theory / Statistics / Bioinformatics / Hidden Markov model / Cybernetics / State space / Empirical Bayes method / Mathematical model / Mathematics / Markov models / Control theory


A semiparametric Bayesian approach to Wiener system identification Fredrik Lindsten ∗ Thomas B. Sch¨ on ∗ Michael I. Jordan ∗∗ ∗
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Document Date: 2012-05-31 00:39:24

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City

Kyoto / Cambridge / Milan / Saint-Malo / Springer / /

Company

MIT Press / Monte Carlo / /

Country

France / Japan / United States / Italy / /

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Facility

Massachusetts Institute of Technology / University of California / /

IndustryTerm

subspace identification algorithm / nonlinear dynamical systems / approximate solution / nonlinear systems / closed form solution / statistical inference tool / interconnected linear dynamical systems / computing / linear systems / /

Organization

Swedish Research Council / Royal Statistical Society / World Congress / Linneaus Center / American Statistical Association / University of California / Berkeley / Massachusetts Institute of Technology / CADICS / Division of Automatic Control / /

Person

Thomas B. Sch / Emily B. Fox / P. Van Overschee / Van Overschee / Fredrik Lindsten / Michael I. Jordan / /

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Position

GP model for the static nonlinearity / model / h / model for the static nonlinearity / /

ProvinceOrState

New York / Massachusetts / /

PublishedMedium

Acta Mathematica / Journal of the Royal Statistical Society / Machine Learning / Journal of the American Statistical Association / /

Technology

GPS / Machine Learning / simulation / subspace identification algorithm / PDF / /

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