Search for dissertations about: "Håkan Ljung"

Found 4 swedish dissertations containing the words Håkan Ljung.

  2. 1. A logistic regression model having independent variables measured with error : a predictiv approach

    Author : Håkan Ljung; Uppsala universitet; []
    Keywords : ;

    Abstract : .... READ MORE

  4. 2. Semi Markov chain Monte Carlo

    Author : Håkan Ljung; Uppsala universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Mathematics; Adaptive simulation; error-in-the-variables; Kullback-Leibler divergence; Markov chain simulation; Markov chain Monte Carlo; semi-regenerative; MATEMATIK; MATHEMATICS; MATEMATIK; matematisk statistik; Mathematical Statistics;

    Abstract : The first paper introduces a new simulation technique, called semi Markov chain Monte Carlo, suitable for estimating the expectation of a fixed function over a distribution π, Eπf(χ). Given a Markov chain with stationary distribution p, for example a Markov chain corresponding to a Markov chain Monte Carlo algorithm, an embedded Markov renewal process is used to divide the trajectory into different parts. READ MORE

  5. 3. Complexity Issues, Validation and Input Design for Control in System Identification

    Author : Märta Barenthin Syberg; Bo Wahlberg; Håkan Hjalmarsson; Lennart Ljung; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Automatic control; Reglerteknik;

    Abstract : System identification is about constructing and validating modelsfrom measured data. When designing system identificationexperiments in control applications, there are many aspects toconsider. One important aspect is the choice of model structure.Another crucial issue is the design of input signals. READ MORE

  6. 4. Least Squares Methods for System Identification of Structured Models

    Author : Miguel Galrinho; Håkan Hjalmarsson; Lennart Ljung; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY;

    Abstract : The purpose of system identification is to build mathematical models for dynamical systems from experimental data. With the current increase in complexity of engineering systems, an important challenge is to develop accurate and computationally efficient algorithms. READ MORE