From Model-Based to Data-Driven Filter Design

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]

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Titolo: From Model-Based to Data-Driven Filter Design
Autori: 
MILANESE, Mario
RUIZ PALACIOS, FREDY ORLANDO
TARAGNA, MICHELE
Data di pubblicazione: 2013
Titolo del libro: Bounded Noises in Physics, Biology, and Engineering. Modeling and Simulation in Science, Engineering and Technology
Serie: 
MODELING AND SIMULATION IN SCIENCE, ENGINEERING AND TECHNOLOGY  
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)

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Utilizza questo identificativo per citare o creare un link a questo documento:
http://hdl.handle.net/11583/2518614
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