Course: ELEC-E8105 - Non-linear Filtering and Parameter Estimation P, 09.01.2019-10.04.2019, Topic: Materials

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

Topic outline

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