Sökning: "State-space filter"
Visar resultat 21 - 25 av 34 avhandlingar innehållade orden State-space filter.
21. Learning control for flex-fuel CI engine and fuel cell
Sammanfattning : This thesis investigated the modeling and control problems in the context of the flex-fuel compression-ignition (CI) engine and fuel cell, which shows great potential in the transition from fossil fuel to renewable energy sources.The modeling parts included the flex-fuel engine combustion process and intake system, and the system scale fuel cell model. LÄS MER
22. Efficient Structure and Motion: Path Planning, Uncertainty and Sparsity
Sammanfattning : This thesis explores methods for solving the structure-and-motion problem in computer vision, the recovery of three-dimensional data from a series of two-dimensional image projections. The first paper investigates an alternative state space parametrization for use with the Kalman filter approach to simultaneous localization and mapping, and shows it has superior convergence properties compared with the state-of-the-art. LÄS MER
23. On inference in partially observed Markov models using sequential Monte Carlo methods
Sammanfattning : This thesis concerns estimation in partially observed continuous and discrete time Markov models and focus on both inference about the conditional distribution of the unobserved process as well as parameter inference for the dynamics of the unobserved process. Paper A concerns calibration of advanced stock price models, in particular the Bates and NIG-CIR models, using options data observed through bid-ask spreads. LÄS MER
24. Seasonal Adjustment and Dynamic Linear Models
Sammanfattning : Dynamic Linear Models are a state space model framework based on the Kalman filter. We use this framework to do seasonal adjustments of empirical and artificial data. A simple model and an extended model based on Gibbs sampling are used and the results are compared with the results of a standard seasonal adjustment method. LÄS MER
25. Non-Linear System Identification with Neural Networks
Sammanfattning : This thesis addresses the non-linear system identification problem, and in particular, investigates the use of neural networks in system identification. An overview of different possible mode! structures is given in a common framework. LÄS MER