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Visar resultat 1 - 5 av 13 avhandlingar som matchar ovanstående sökkriterier.
1. Spatio-Temporal Estimation for Mixture Models and Gaussian Markov Random Fields - Applications to Video Analysis and Environmental Modelling
Sammanfattning : In this thesis computationally intensive methods are used to estimate models and to make inference for large, spatio-temporal data sets. The thesis is divided into two parts: the first two papers are concerned with video analysis, while the last three papers model and investigate environmental data from the Sahel area in northern Africa. LÄS MER
2. Sensor Fusion and Control Applied to Industrial Manipulators
Sammanfattning : One of the main tasks for an industrial robot is to move the end-effector in a predefined path with a specified velocity and acceleration. Different applications have different requirements of the performance. LÄS MER
3. Inference techniques for stochastic nonlinear system identification with application to the Wiener-Hammerstein models
Sammanfattning : Stochastic nonlinear systems are a specific class of nonlinear systems where unknown disturbances affect the system's output through a nonlinear transformation. In general, the identification of parametric models for this kind of systems can be very challenging. LÄS MER
4. Pharmacometric Methods and Novel Models for Discrete Data
Sammanfattning : Pharmacodynamic processes and disease progression are increasingly characterized with pharmacometric models. However, modelling options for discrete-type responses remain limited, although these response variables are commonly encountered clinical endpoints. Types of data defined as discrete data are generally ordinal, e.g. LÄS MER
5. Rao-Blackwellised particle methods for inference and identification
Sammanfattning : We consider the two related problems of state inference in nonlinear dynamical systems and nonlinear system identification. More precisely, based on noisy observations from some (in general) nonlinear and/or non-Gaussian dynamical system, we seek to estimate the system state as well as possible unknown static parameters of the system. LÄS MER