Journal article
Uncertainty and filtering of hidden Markov models in discrete time
- Abstract:
- We consider the problem of filtering an unseen Markov chain from noisy observations, in the presence of uncertainty regarding the parameters of the processes involved. Using the theory of nonlinear expectations, we describe the uncertainty in terms of a penalty function, which can be propagated forward in time in the place of the filter. We also investigate a simple control problem in this context.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Version of record, 604.4KB, Terms of use)
-
- Publisher copy:
- 10.1186/s41546-020-00046-x
Authors
- Publisher:
- SpringerOpen
- Journal:
- Probability, Uncertainty and Quantitative Risk More from this journal
- Volume:
- 5
- Article number:
- 4
- Publication date:
- 2020-06-03
- Acceptance date:
- 2020-02-28
- DOI:
- EISSN:
-
2367-0126
- Language:
-
English
- Keywords:
- Pubs id:
-
867003
- Local pid:
-
pubs:867003
- Deposit date:
-
2020-03-10
Terms of use
- Copyright holder:
- Samuel N. Cohen
- Copyright date:
- 2020
- Rights statement:
- © The Author 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
- Licence:
- CC Attribution (CC BY)
If you are the owner of this record, you can report an update to it here: Report update to this record