Search for dissertations about: "gaussian mixture"
Showing result 1 - 5 of 51 swedish dissertations containing the words gaussian mixture.
-
1. Spatial Mixture Models with Applications in Medical Imaging and Spatial Point Processes
Abstract : Finite mixture models have proven to be a great tool for both modeling non-standard probability distributions and for classification problems (using the latent variable interpretation). In this thesis we are building spatial models by incorporating spatially dependent categorical latent random fields in a hierarchical manner similar to that of finite mixture models. READ MORE
-
2. Towards Low-Complexity Vector Quantization
Abstract : This thesis is about constructing low-complexity, yet high-performance, vector quantizers (VQs) for 'real-world' sources. Knowledge concerning the source is extracted from a finite training set. In contrast with conventional VQ design procedures, we use the training set to estimate a statistical model for the source. READ MORE
-
3. Bayesian Cluster Analysis : Some Extensions to Non-standard Situations
Abstract : The Bayesian approach to cluster analysis is presented. We assume that all data stem from a finite mixture model, where each component corresponds to one cluster and is given by a multivariate normal distribution with unknown mean and variance. READ MORE
-
4. On flexible random field models for spatial statistics: Spatial mixture models and deformed SPDE models
Abstract : Spatial random fields are one of the key concepts in statistical analysis of spatial data. The random field explains the spatial dependency and serves the purpose of regularizing interpolation of measured values or to act as an explanatory model. READ MORE
-
5. Practical methods for Gaussian mixture filtering and smoothing
Abstract : In many applications, there is an interest in systematically and sequentially estimating quantities of interest in a dynamical system, using indirect and inaccurate sensor observations. There are three important sub-problems of sequential estimation: prediction, filtering and smoothing. READ MORE