Archivio Istituzionale della RicercaThis paper investigates the filter design problem for linear time-invariant dynamic systems when no mathematical model is available, but a set of initial experiments can be performed where also the variable to be estimated is measured. Two-step and direct approaches are considered within both a stochastic and a deterministic framework and optimal or suboptimal solutions are reviewed.
From Model-Based to Data-Driven Filter Design / Milanese, Mario; RUIZ PALACIOS, FREDY ORLANDO; Taragna, Michele (MODELING AND SIMULATION IN SCIENCE, ENGINEERING AND TECHNOLOGY). - In: Bounded Noises in Physics, Biology, and Engineering. Modeling and Simulation in Science, Engineering and Technology / d'Onofrio A.; ed.. - STAMPA. - Boston : Birkhäuser, 2013. - ISBN 978-1-4614-7384-8. - pp. 273-285 [10.1007/978-1-4614-7385-5_16]
From Model-Based to Data-Driven Filter Design
MILANESE, Mario;RUIZ PALACIOS, FREDY ORLANDO;TARAGNA, MICHELE
2013
Abstract
This paper investigates the filter design problem for linear time-invariant dynamic systems when no mathematical model is available, but a set of initial experiments can be performed where also the variable to be estimated is measured. Two-step and direct approaches are considered within both a stochastic and a deterministic framework and optimal or suboptimal solutions are reviewed.
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https://hdl.handle.net/11583/2518614
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