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Träfflista för sökning "WFRF:(Bottegal Giulio) srt2:(2018)"

Sökning: WFRF:(Bottegal Giulio) > (2018)

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1.
  • Everitt, Niklas, et al. (författare)
  • An empirical Bayes approach to identification of modules in dynamic networks
  • 2018
  • Ingår i: Automatica. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0005-1098 .- 1873-2836. ; 91, s. 144-151
  • Tidskriftsartikel (refereegranskat)abstract
    • We present a new method of identifying a specific module in a dynamic network, possibly with feedback loops. Assuming known topology, we express the dynamics by an acyclic network composed of two blocks where the first block accounts for the relation between the known reference signals and the input to the target module, while the second block contains the target module. Using an empirical Bayes approach, we model the first block as a Gaussian vector with covariance matrix (kernel) given by the recently introduced stable spline kernel. The parameters of the target module are estimated by solving a marginal likelihood problem with a novel iterative scheme based on the Expectation-Maximization algorithm. Additionally, we extend the method to include additional measurements downstream of the target module. Using Markov Chain Monte Carlo techniques, it is shown that the same iterative scheme can solve also this formulation. Numerical experiments illustrate the effectiveness of the proposed methods.
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2.
  • Risuleo, Riccardo Sven, 1986-, et al. (författare)
  • Approximate Maximum-likelihood Identification of Linear Systems from Quantized Measurements⁎
  • 2018
  • Ingår i: IFAC-PapersOnLine. - : Elsevier B.V.. - 2405-8963. ; 51:15, s. 724-729
  • Tidskriftsartikel (refereegranskat)abstract
    • We analyze likelihood-based identification of systems that are linear in the parameters from quantized output data; in particular, we propose a method to find approximate maximum-likelihood and maximum-a-posteriori solutions. The method consists of appropriate least-squares projections of the middle point of the active quantization intervals. We show that this approximation maximizes a variational approximation of the likelihood and we provide an upper bound for the approximation error. In a simulation study, we compare the proposed method with the true maximum-likelihood estimate of a finite impulse response model. 
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  • Resultat 1-2 av 2
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tidskriftsartikel (2)
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refereegranskat (2)
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Bottegal, Giulio (2)
Hjalmarsson, Håkan (1)
Hjalmarsson, Håkan, ... (1)
Risuleo, Riccardo Sv ... (1)
Everitt, Niklas (1)
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Kungliga Tekniska Högskolan (2)
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Engelska (2)
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2018 (2)Ta bort avgränsningen

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