Tutorial 3: Linear Dynamical Systems and the Kalman Filter
Tutorial 3: Linear Dynamical Systems and the Kalman Filter
This tutorial covers how to infer a latent model when our states are continuous. Particular attention is paid to the Kalman filter and its mathematical foundation.
Topics covered in this lesson
- Linear dynamical systems
- Kalman Filtering
- Fitting eye gaze data
- Review on Gaussian joint, marginal, and conditional distributions
- Kalman smoothing
- The Expectation-Maximization (EM) Algorithm
External Links
Prerequisites
Experience with Python Programming Language
Back to the course