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Sökning: WFRF:(Hjalmarsson Håkan) > (2015-2018) > Schoukens Johan

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1.
  • Hägg, Per, et al. (författare)
  • The Transient Impulse Response Modeling Method for Non-parametric System Identication
  • 2016
  • Ingår i: Automatica. - : Elsevier. - 0005-1098 .- 1873-2836. ; 68, s. 314-328
  • Tidskriftsartikel (refereegranskat)abstract
    • A method for the nonparametric estimation of the Frequency Response Function (FRF) was introduced in [5] and latercalled Transient Impulse Response Modeling Method (trimm). We present here a slightly improved version of the originalmethod and, more importantly, we thoroughly analyze the method in terms of bias and variance errors. This analysis leads toguidelines for the choice of the design parameters of the trimm method. Our theoretical expressions for the bias and varianceerrors are validated by simulations which, at the same time, highlight the eect of the design parameters on the performanceof the method.
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2.
  • Risuleo, Riccardo Sven, 1986- (författare)
  • Bayesian learning of structured dynamical systems
  • 2018
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • In this thesis, we propose some Bayesian approaches to the identificationof structured dynamical systems. In particular, we consider block-orientedmodels in which a complex system is built starting from simple linear andnonlinear building blocks. Each building block has a Gaussian-process modelthat can be used to include prior information into the learning problem.The learning is then guided by Bayes’ theorem. In particular, we use anempirical Bayes approach to perform the identification of models with hyper-parameters. As the models considered in this thesis are, in general, intractable,we propose several approximation methods based on variational Bayes andMarkov-chain Monte Carlo sampling. To estimate the hyperpameters, wepropose iterative algorithms based on variational expectation maximizationand stochastic-approximation expectation maximization.The main contribution of the thesis is developed in Part II. Here, we firststudy uncertain-input systems and Wiener systems as the typical Gaussian-process models of two-block cascades. In addition, we propose a robust ap-proach for uncertain-input systems with outliers in the measurements. Then,we proceed considering more complex structures such as acyclic networksof linear dynamical systems, feedback interconnections of linear systems,and three-block nonlinear structures such as the Wiener-Hammerstein andHammerstein-Wiener cascades. Finally, we consider some problems relatedto quantized measurements: we propose an approximate estimator and weprovide a rigorous analysis of the statistical properties of quantization noise.All the models and methods are discussed in detail and accompanied byalgorithms and implementation details. The proposed techniques are shownin several simulation examples.
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  • Resultat 1-2 av 2
Typ av publikation
tidskriftsartikel (1)
doktorsavhandling (1)
Typ av innehåll
övrigt vetenskapligt/konstnärligt (1)
refereegranskat (1)
Författare/redaktör
Hjalmarsson, Håkan (2)
Risuleo, Riccardo Sv ... (1)
Hägg, Per (1)
Gevers, Michel (1)
Schoukens, Johan, Pr ... (1)
Lärosäte
Kungliga Tekniska Högskolan (2)
Språk
Engelska (2)
Forskningsämne (UKÄ/SCB)
Teknik (2)

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