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AUTOMATICA
2010

Bayesian system identification via Markov chain Monte Carlo techniques

9 years 6 months ago
Bayesian system identification via Markov chain Monte Carlo techniques
The work here explores new numerical methods for supporting a Bayesian approach to parameter estimation of dynamic systems. This is primarily motivated by the goal of providing accurate quantification of estimation error that is valid for arbitrary, and hence even very short length data records. The main innovation is the employment of the Metropolis
Brett Ninness, Soren J. Henriksen
Added 08 Dec 2010
Updated 08 Dec 2010
Type Journal
Year 2010
Where AUTOMATICA
Authors Brett Ninness, Soren J. Henriksen
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