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.
From Model-Based to Data-Driven Filter Design / Milanese, M.; Ruiz Palacios, F.O.; Taragna, M.. - STAMPA. - (2013), pp. 273-285. [10.1007/978-1-4614-7385-5_16]
Titolo: | From Model-Based to Data-Driven Filter Design | |
Autori: | ||
Data di pubblicazione: | 2013 | |
Titolo del libro: | Bounded Noises in Physics, Biology, and Engineering. Modeling and Simulation in Science, Engineering and Technology | |
Serie: | ||
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. | |
ISBN: | 978-1-4614-7384-8 | |
Appare nelle tipologie: | 2.1 Contributo in volume (Capitolo o Saggio) |
File in questo prodotto:
File | Descrizione | Tipologia | Licenza | |
---|---|---|---|---|
PDF_editoriale.pdf | From Model-Based to Data-Driven Filter Design (Editorial version) | 2. Post-print / Author's Accepted Manuscript | Non Pubblico - Accesso privato/ristretto | Administrator Richiedi una copia |
Utilizza questo identificativo per citare o creare un link a questo documento:
http://hdl.handle.net/11583/2518614
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.