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ELEC-E8105 - Non-linear Filtering and Parameter Estimation P, 09.01.2019-10.04.2019

This course space end date is set to 10.04.2019 Search Courses: ELEC-E8105

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Syllabus
 

Materials

  • Materials

    Materials

    Course book

    The course book can be found in the following link and is also available, e.g., in Amazon:

    http://users.aalto.fi/~ssarkka/pub/cup_book_online_20131111.pdf

    Additional materials (examples from the book, etc.) can be found on the book's homepage (tab "Resources"):

    http://www.cambridge.org/fi/academic/subjects/statistics-probability/applied-probability-and-stochastic-networks/bayesian-filtering-and-smoothing

    Lecture slides

    After each lecture, the lecture slides will be added below in PDF form.

    • icon for activity
      FileLecture 0: Course Arrangements File
      PDF document
    • icon for activity
      FileLecture 1: Overview of Bayesian Modeling of Time-Varying Systems File
      PDF document
    • icon for activity
      FileLecture 2: From Linear Regression to Kalman Filter and Beyond File
      PDF document
    • icon for activity
      FileiPad notes from lecture 16.1. File
      PDF document
    • icon for activity
      FileRecursive linear regression code File
      Text file
    • icon for activity
      FileLecture 3: Bayesian Filtering Equations and Kalman Filter File
      PDF document
    • icon for activity
      FileiPad notes from lecture 23.1. File
      PDF document
    • icon for activity
      FileCar tracking Matlab example File
      Text file
    • icon for activity
      FileLecture 4: Extended Kalman Filter and Statistical Linearization File
      PDF document
    • icon for activity
      FileiPad Notes from Lecture 30.1. File
      PDF document
    • icon for activity
      FilePendulum EKF code File
      Text file
    • icon for activity
      FilePendulum simulation code File
      Text file
    • icon for activity
      FileLecture 5: Unscented Kalman filter, Gaussian Filter, GHKF and CKF File
      PDF document
    • icon for activity
      FileiPad Notes from Lecture 6.2. File
      PDF document
    • icon for activity
      FilePendulum UKF code File
      Text file
    • icon for activity
      FilePendulum CKF code File
      Text file
    • icon for activity
      FilePendulum GHKF code File
      Text file
    • icon for activity
      FileLecture 6: Particle Filtering File
      PDF document
    • icon for activity
      FileiPad notes from lecture 13.2. File
      PDF document
    • icon for activity
      FileParticle filter example File
      Text file
    • icon for activity
      FileGaussian random number routine File
      Text file
    • icon for activity
      FileStratified resampling File
      Text file
    • icon for activity
      FileLecture 7: Rao–Blackwellized Particle Filtering File
      PDF document
    • icon for activity
      FileiPad Notes from lecture 27.2. File
      PDF document
    • icon for activity
      FileLecture 8: Bayesian optimal smoother, Rauch-Tung-Striebel smoothing File
      PDF document
    • icon for activity
      FileiPad Notes from lecture 6.3.2019 File
      PDF document
    • icon for activity
      FileCar tracking example (again with small mods) File
      Text file
    • icon for activity
      FileLecture 9: Gaussian and Particle Smoothers File
      PDF document
    • icon for activity
      File iPad Notes from lecture 13.3.2019 File
      PDF document
    • icon for activity
      FolderFiltering & smoothing codes Folder
    • icon for activity
      FileLecture 10: Bayesian Estimation of Parameters in State Space Models File
      PDF document
    • icon for activity
      FileiPad Notes from lecture 20.3.2019 File
      PDF document
    • icon for activity
      FileParameter estimation example File
      Text file

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  • ELEC-E8105 - Non-linear Filtering and Parameter Estimation P, 09.01.2019-10.04.2019
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  • Schools
    • School of Arts, Design, and Architecture (ARTS)
    • School of Business (BIZ)
    • School of Chemical Engineering (CHEM)
    • –sGuides for students (CHEM)
    • – Instructions for report writing (CHEM)
    • School of Electrical Engineering (ELEC)
    • School of Engineering (ENG)
    • School of Science (SCI)
    • Language Centre
    • Open University
    • Library
    • Aalto university pedagogical training program
    • UNI (exams)
    • Sandbox
  • Service Links
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    • - MyCourses instructions for Teachers
    • - MyCourses instructions for Students
    • - Teacher book your online session with a specialist
    • - Digital tools for teaching
    • - Personal data protection instructions for teachers
    • - Workspace for thesis supervision
    • Sisu
    • Student guide
    • Courses.aalto.fi
    • Library Services
    • - Resourcesguides
    • - Imagoa / Open science and images
    • IT Services
    • Campus maps
    • - Search spaces and see opening hours
    • Restaurants in Otaniemi
    • ASU Aalto Student Union
    • Aalto Marketplace
  • ALLWELL?
    • Study Skills
    • Guidance and support for students
    • Starting Point of Wellbeing
    • About AllWell? study well-being questionnaire
  •   ‎(en)‎
    •   ‎(en)‎
    •   ‎(fi)‎
    •   ‎(sv)‎