Nonlinear state and parameter estimation of spatially distributed systems

• Autore: Sawo Felix
• Pubblicazione: KIT Scientific Publishing, 2009
• Descrizione fisica: 1 online resource (XI, 153 p. p.)
• Soggetto non controllato: distributed-parameter system; nonlinear estimation; sensor network
• Sommario/riassunto: In this thesis two probabilistic model-based estimators are introduced that allow the reconstruction and identification of space-time continuous physical systems. The Sliced Gaussian Mixture Filter (SGMF) exploits linear substructures in mixed linear/nonlinear systems, and thus is well-suited for identifying various model parameters. The Covariance Bounds Filter (CBF) allows the efficient estimation of widely distributed systems in a decentralized fashion.
• Titolo autorizzato: Nonlinear state and parameter estimation of spatially distributed systems
• ISBN: 1000011485
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910346924403321
• Lo trovi qui: Univ. Federico II