Sökning: "Riccardo Sven Risuleo"

Hittade 3 avhandlingar innehållade orden Riccardo Sven Risuleo.

1. 1. Bayesian learning of structured dynamical systems

   Författare :Riccardo Sven Risuleo; Håkan Hjalmarsson; Johan Schoukens; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; system identification; bayesian learning; machine learning; Gaussian processes; Electrical Engineering; Elektro- och systemteknik;

   Sammanfattning : 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. LÄS MER

3. 2. System identification with input uncertainties : an EM kernel-based approach

   Författare :Riccardo Sven Risuleo; Håkan Hjalmarsson; Alessandro Chiuso; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Electrical Engineering; Elektro- och systemteknik;

   Sammanfattning : Many classical problems in system identification, such as the classical predictionerror method and regularized system identification, identification of Hammersteinand cascaded systems, blind system identification, as well as errors-in-variablesproblems and estimation with missing data, can be seen as particular instancesof the general problem of the identification of systems with limited information.In this thesis, we introduce a framework for the identification of linear dynamicalsystems subject to inputs that are not perfectly known. LÄS MER

4. 3. 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