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On Data-driven Mult...
On Data-driven Multistep Subspace-based Linear Predictors
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- Cescon, Marzia (författare)
- Lund University,Lunds universitet,Institutionen för reglerteknik,Institutioner vid LTH,Lunds Tekniska Högskola,Department of Automatic Control,Departments at LTH,Faculty of Engineering, LTH
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- Johansson, Rolf (författare)
- Lund University,Lunds universitet,Institutionen för reglerteknik,Institutioner vid LTH,Lunds Tekniska Högskola,Department of Automatic Control,Departments at LTH,Faculty of Engineering, LTH
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(creator_code:org_t)
- 2011
- 2011
- Engelska 6 s.
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Ingår i: 18th IFAC World Congress. - 1474-6670. - 9783902661937 ; 44:1, s. 11447-11452
- Relaterad länk:
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http://dx.doi.org/10...
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https://lup.lub.lu.s...
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https://doi.org/10.3...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
Nyckelord
- Subspace identification
- prediction error methods
- biological systems
Publikations- och innehållstyp
- kon (ämneskategori)
- ref (ämneskategori)
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