Format:
xi, 101 Seiten
,
Diagramme
Content:
Data assimilation has been an active area of research in recent years, owing to its wide utility. At the core of data assimilation are filtering, prediction, and smoothing procedures. Filtering entails incorporation of measurements' information into the model to gain more insight into a given state governed by a noisy state space model. Most natural laws are governed by time-continuous nonlinear models. For the most part, the knowledge available about a model is incomplete; and hence uncertainties are approximated by means of probabilities. Time-continuous filtering, therefore, holds promise for wider usefulness, for it offers a means of combining noisy measurements with imperfect model to provide more insight on a given state. The solution to time-continuous nonlinear Gaussian filtering problem is provided for by the Kushner-Stratonovich equation. Unfortunately, the Kushner-Stratonovich equation lacks a closed-form solution. Moreover, the numerical approximations based on Taylor expansion above third order are fraught with ...
Note:
Dissertation Universität Potsdam 2019
Additional Edition:
Erscheint auch als Online-Ausgabe Angwenyi, David Time-continuous state and parameter estimation with application to hyperbolic SPDEs Potsdam, 2019
Language:
English
Keywords:
Stochastische Differentialgleichung
;
Hochschulschrift
