Sökning: "Elektroteknik med inriktning mot signalbehandling"

Visar resultat 26 - 30 av 32 avhandlingar innehållade orden Elektroteknik med inriktning mot signalbehandling.

  1. 26. Exploiting conjugacy in state-space models with sequential Monte Carlo

    Författare :Anna Wigren; Fredrik Lindsten; Umberto Picchini; Uppsala universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Electrical Engineering with specialization in Signal Processing; Elektroteknik med inriktning mot signalbehandling;

    Sammanfattning : Many processes we encounter in our daily lives are dynamical systems that can be described mathematically using state-space models. Exact inference of both states and parameters in these models is, in general, intractable. LÄS MER

  2. 27. Sequential Monte Carlo methods for conjugate state-space models

    Författare :Anna Wigren; Fredrik Lindsten; Lawrence Murray; Riccardo Sven Risuleo; Simon Maskell; Uppsala universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Sequential Monte Carlo; Particle filter; Markov chain Monte Carlo; Conjugacy; State-space model; Probabilistic programming; Electrical Engineering with specialization in Signal Processing; Elektroteknik med inriktning mot signalbehandling;

    Sammanfattning : Bayesian inference in state-space models requires the solution of high-dimensional integrals, which is intractable in general. A viable alternative is to use sample-based methods, like sequential Monte Carlo, but this introduces variance into the inferred quantities that can sometimes render the estimates useless. LÄS MER

  3. 28. Machine learning with state-space models, Gaussian processes and Monte Carlo methods

    Författare :Andreas Svensson; Thomas B. Schön; Fredrik Lindsten; Carl Edward Rasmussen; Uppsala universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Machine learning; State-space models; Gaussian processes; Elektroteknik med inriktning mot reglerteknik; Electrical Engineering with specialization in Automatic Control;

    Sammanfattning : Numbers are present everywhere, and when they are collected and recorded we refer to them as data. Machine learning is the science of learning mathematical models from data. Such models, once learned from data, can be used to draw conclusions, understand behavior, predict future evolution, and make decisions. LÄS MER

  4. 29. Data-Driven Methods for Microwave Sensor Devices in Musculoskeletal Diagnostics

    Författare :Viktor Mattsson; Robin Augustine; Mauricio D. Perez; Roger Karlsson; Paul Meaney; Joseph Costantine; Uppsala universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Machine Learning; Microwave Sensors; Data-Driven Modeling; Statistical Analysis; Maskininlärning; Mikrovågssensorer; Datadriven modellering; Statistisk Analys; Teknisk fysik med inriktning mot elektronik; Engineering Science with specialization in Electronics;

    Sammanfattning : Microwave sensors can be used within medicine as they use non-ionizing radiation, are often low cost, and can be designed for a specific purpose. The application of microwave sensors for diagnostics and monitoring can be improved using appropriate data analysis. The multi-layered structure of the human body makes the measurements on people complex. LÄS MER

  5. 30. Active Noise Control in Aircraft : Algorithms and Applications

    Författare :Sven Johansson; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; active noise control; feedforward control; filtere-x lms algorithm; complex lms; multichannel system; multiple reference; aircraft; headset;

    Sammanfattning : The thesis consists of five papers which are divided into three main parts. Parts A and B deal with active noise control in a propeller aircraft application, whereas Part C deals with active noise control in a helicopter application. LÄS MER