On Data-driven Multistep Subspace-based Linear Predictors
(2011) 18th IFAC World Congress, 2011 In IFAC Proceedings Volumes 44(1). p.11447-11452- Abstract
- The focus of this contribution is the estimation of multi-step-ahead linear multivariate predictors of the output making use of finite input-output data sequences. Different strategies will be presented, the common factor being the exploitations of geometric operations on appropriate subspaces spanned by the data. In order to test the capabilities of the proposed methods in predicting new data, a real-life example, namely, the case of blood glucose prediction in Type 1 Diabetes patients, is provided.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2203125
- author
- Cescon, Marzia LU and Johansson, Rolf LU
- organization
- publishing date
- 2011
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Subspace identification, prediction error methods, biological systems
- host publication
- 18th IFAC World Congress
- series title
- IFAC Proceedings Volumes
- volume
- 44
- issue
- 1
- pages
- 6 pages
- publisher
- Elsevier
- conference name
- 18th IFAC World Congress, 2011
- conference location
- Milan, Italy
- conference dates
- 2011-08-28 - 2011-09-02
- external identifiers
-
- scopus:84866747262
- ISSN
- 1474-6670
- ISBN
- 978-3-902661-93-7
- DOI
- 10.3182/20110828-6-IT-1002.02828
- project
- DIAdvisor
- language
- English
- LU publication?
- yes
- id
- 1ca0f1ee-67b2-4f9a-86af-d2324f1cc140 (old id 2203125)
- date added to LUP
- 2016-04-04 14:23:46
- date last changed
- 2024-01-13 17:30:43
@inproceedings{1ca0f1ee-67b2-4f9a-86af-d2324f1cc140, abstract = {{The focus of this contribution is the estimation of multi-step-ahead linear multivariate predictors of the output making use of finite input-output data sequences. Different strategies will be presented, the common factor being the exploitations of geometric operations on appropriate subspaces spanned by the data. In order to test the capabilities of the proposed methods in predicting new data, a real-life example, namely, the case of blood glucose prediction in Type 1 Diabetes patients, is provided.<br/>}}, author = {{Cescon, Marzia and Johansson, Rolf}}, booktitle = {{18th IFAC World Congress}}, isbn = {{978-3-902661-93-7}}, issn = {{1474-6670}}, keywords = {{Subspace identification; prediction error methods; biological systems}}, language = {{eng}}, number = {{1}}, pages = {{11447--11452}}, publisher = {{Elsevier}}, series = {{IFAC Proceedings Volumes}}, title = {{On Data-driven Multistep Subspace-based Linear Predictors}}, url = {{https://lup.lub.lu.se/search/files/22837564/ifac2011_marzia_final.pdf}}, doi = {{10.3182/20110828-6-IT-1002.02828}}, volume = {{44}}, year = {{2011}}, }