Search for dissertations about: "Function estimation"
Showing result 1 - 5 of 428 swedish dissertations containing the words Function estimation.
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1. Position Estimation and Tracking in Colloidal Particle Microscopy
Abstract : This thesis presents methods for estimating the locations (including depth) of spherical colloidal particles in images recorded in video microscopy. Understanding the behavior of colloidal interactions and diffusion is of crucial importance in a vast number of areas. READ MORE
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2. On the Mean Square Error of Transfer Function Estimates with Applications to Control
Abstract : In this report we study the mean square error of transfer function estimates obtained by identification. The model quality is related to the use of models in regulator design, and the properties of affecting the bias part of the mean square error, both in fixed parameter control and adaptive control. READ MORE
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3. Recursive Bayesian Estimation : Navigation and Tracking Applications
Abstract : Recursive estimation deals with the problem of extracting information about parameters, or states, of a dynamical system in real time, given noisy measurements of the system output. Recursive estimation plays a central role in many applications of signal processing, system identification and automatic control. READ MORE
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4. EM Estimation in Phase Type Models
Abstract : This thesis consists of four articles whose theme in common is the class of phase type distributions. In the first article an EM algorithm is presented to estimate the parameters of a phase type distribution of fixed order. Also, it is shown that the algorithm can be used to approximate other continuous distributions by phase type distributions. READ MORE
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5. Low-angle estimation : Models, methods and bounds
Abstract : In this work we study the performance of elevation estimators and lower bounds on the estimation error variance for a low angle target in a smooth sea scenario using an array antenna. The article is structured around some key assumptions on multipath knowledge, signal parameterization and noise covariance, giving the reader a framework in which Maximum Likelihood estimators exploiting different á priori information can be found. READ MORE