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Active learning for linear parameter-varying system identification
Robert Chin
, Alejandro I. Maass
, Nalika Ulapane
, Chris Manzie
, Iman Shames
, Dragan Nesic
,
Jonathon E. Rowe
, Hayato Nakada
Computer Science
Research output
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Keyphrases
System Identification
100%
Active Learning
100%
Linear Parameter-varying Systems
100%
Model Uncertainty
66%
Operating Point
33%
Multiple-input multiple-output System
33%
Design of Experiments
33%
Overall Modeling
33%
Gaussian Process Regression
33%
Path Model
33%
Identified Model
33%
Diesel Engine Air Path
33%
Scheduling Parameter
33%
Local Linear Model
33%
Probabilistic Features
33%
Engineering
Model Uncertainty
100%
Diesel Engine
50%
Operating Point
50%
Output System
50%
Design of Experiments
50%
Gaussians
50%
Multiple-Input Multiple-Output
50%
Path Model
50%
Air Path
50%
Scheduling Parameter
50%
Computer Science
System Identification
100%
Active Learning
100%
Linear Parameter
100%
Model Uncertainty
66%
MIMO Systems
33%
Scheduling Parameter
33%
Operating Point
33%
Chemical Engineering
MIMO Systems
100%