Sökning: "Hidden Markov Model"
Visar resultat 1 - 5 av 58 avhandlingar innehållade orden Hidden Markov Model.
- Detta är en avhandling från KTH Royal Institute of Technology
Sammanfattning : The hidden Markov model (HMM) is one of the workhorse tools in, for example, statistical signal processing and machine learning. It has found applications in a vast number of fields, ranging all the way from bioscience to speech recognition to modeling of user interactions in social networks. LÄS MER
- Detta är en avhandling från Mathematical Statistics, Centre for Mathematical Sciences, Lund University
Sammanfattning : Rainflow cycles are often used in fatigue analysis of materials for describing the variability of applied loads. Therefore, an important characteristic of a random load process is the intensity of rainflow cycles, also called the expected rainflow matrix (RFM), which can be used for evaluation of the fatigue life. LÄS MER
- Detta är en avhandling från Centre for Mathematical Sciences, Lund University
Sammanfattning : The main motivation for this thesis, however not the only one, is the search for models for traffic in telecommunication networks. Traffic characterization and modeling are of great importance in the analysis and dimensioning of communication systems. During the last decades we have experienced an explosive growth of our telecommunication networks. LÄS MER
- Detta är en avhandling från Linköping : Linköping University
Sammanfattning : Segmentation of images in the context of model based stochastic techniques is connected with high, very often unpracticle computational complexity. The objective with this thesis is to take the models used in model based image processing, simplify and use them in suboptimal, but not computationally demanding algorithms. LÄS MER
- Detta är en avhandling från Umeå : Umeå University
Sammanfattning : This thesis presents work on methods for the estimation of computed tomography (CT) images from magnetic resonance (MR) images for a number of diagnostic and therapeutic workflows. The study also demonstrates sparse signal recovery method, which is an intermediate method for magnetic resonance image reconstruction. LÄS MER