peterzs / statespacemodels

Mini-course (lecture set) on State Space Models.

State-Space Models - a mini-course

     

This repo contains material for three lectures on state-space models which used to be part of the Advanced Machine Learning course at Linköping University, Sweden. I have separated this part and updated the LaTeX template a bit to make it self-contained.

Recommended reading

• Thrun, Burgard and Fox (2005). Probabilistic Robotics. MIT Press. Main book. My slides use the notation and algorithms from this book.
• Campagnoli, Petrone and Petris (2009). Dynamic Linear Models with R. Springer. Used for the R package and uses a notation more common in (Bayesian) statistics.

Lectures

Lecture 1 - Models, Applications and State inference
Slides

Lecture 2 - Parameter inference and software
Slides

Lecture 3 - Non-Gaussian and nonlinear models and the particle filter
Slides

Computer lab

Lab