Search for dissertations about: "sequential sampling"
Showing result 11 - 15 of 44 swedish dissertations containing the words sequential sampling.
-
11. Bayesian Inference for Nonlinear Dynamical Systems : Applications and Software Implementation
Abstract : The topic of this thesis is estimation of nonlinear dynamical systems, focusing on the use of methods such as particle filtering and smoothing. There are three areas of contributions: software implementation, applications of nonlinear estimation and some theoretical extensions to existing algorithms. READ MORE
-
12. On Bounds and Asymptotics of Sequential Monte Carlo Methods for Filtering, Smoothing, and Maximum Likelihood Estimation in State Space Models
Abstract : This thesis is based on four papers (A-D) treating filtering, smoothing, and maximum likelihood (ML) estimation in general state space models using stochastic particle filters (also referred to as sequential Monte Carlo (SMC) methods). The aim of Paper A is to study the bias of Monte Carlo integration estimates produced by the so-called bootstrap particle filter. READ MORE
-
13. Flow injection systems for process analytical chemistry
Abstract : Flow injection systems have great potential for sample handling and analysis in process analytical chemistry. The flexibility and versatility of flow injection manifolds can he utilized in specific applications of sample conditioning and analysis. READ MORE
-
14. Sequential Monte Carlo for inference in nonlinear state space models
Abstract : Nonlinear state space models (SSMs) are a useful class of models to describe many different kinds of systems. Some examples of its applications are to model; the volatility in financial markets, the number of infected persons during an influenza epidemic and the annual number of major earthquakes around the world. READ MORE
-
15. Learning Sequential Decision Rules in Control Design: Regret-Optimal and Risk-Coherent Methods
Abstract : Engineering sciences deal with the problem of optimal design in the face of uncertainty. In particular, control engineering is concerned about designing policies/laws/algorithms that sequentially take decisions given unreliable data. This thesis addresses two particular instances of optimal sequential decision making for two different problems. READ MORE