Journal
INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION
Volume 2, Issue 3, Pages 239-258Publisher
BEGELL HOUSE INC
DOI: 10.1615/Int.J.UncertaintyQuantification.2012003582
Keywords
Kalman filter; inverse problems; particle filters; fluid mechanics; heat transfer
Funding
- FAPERJ, Brazilian agency
- CAPES, Brazilian agency
- CNPq, Brazilian agency
Ask authors/readers for more resources
The objective of this paper is to introduce applications of Bayesian filters to state estimation problems in heat transfer. A brief description of state estimation problems within the Bayesian framework is presented. The Kalman filter, as well as the following algorithms of the particle filter: sampling importance resampling and auxiliary sampling importance resampling, are discussed and applied to practical problems in heat transfer.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available
Share Paper
