Guillaume Mercère
Main research topics: model learning, learning from data, system identification, estimation theory, state space model, gray box model, linear parameter varying model, linear fractional representation, subspace-based methods, numerical optimization
Main applications: electrical engineering, aeronautics, heat transfer, flexible, cable-driven manipulators, vehicle tire/road interactions and image processing.
Toepassingsgebied/sector
- Computerwetenschappen & IT
Organisatie(s)
Persoonlijke info
opleidingen
Revisiting gray box model learning and Kalman filtering with subspace based model identification
seminarie - Leuven - KU Leuven ESAT STADIUS