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On Data-driven Multistep Subspace-based Linear Predictors

Cescon, Marzia LU and Johansson, Rolf LU orcid (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:
author
and
organization
publishing date
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
2023-04-07 12:29:58
@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}},
}