Nonlinear state and parameter estimation of spatially distributed systems
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 id...
Saved in:
Main Author: | Sawo, Felix (auth) |
---|---|
Format: | Electronic Book Chapter |
Language: | English |
Published: |
KIT Scientific Publishing
2009
|
Series: | Karlsruhe Series on Intelligent Sensor-Actuator-Systems, Universität Karlsruhe / Intelligent Sensor-Actuator-Systems Laboratory
|
Subjects: | |
Online Access: | DOAB: download the publication DOAB: description of the publication |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Framework for Analysis and Identification of Nonlinear Distributed Parameter Systems using Bayesian Uncertainty Quantification based on Generalized Polynomial Chaos
by: Janya-anurak, Chettapong
Published: (2017) -
State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties
by: Noack, Benjamin
Published: (2014) -
Linear Estimation in Interconnected Sensor Systems with Information Constraints
by: Reinhardt, Marc
Published: (2015) -
Nonlinear Systems Design, Analysis, Estimation and Control
Published: (2016) -
Weakly Nonlinear Systems With Applications in Communications Systems /
by: Beffa, Federico
Published: (2024)