Code accompanying my class on nonlinear and data driven estimation

Tips on getting started with GitHub, Google Colab, and Docker

Week 1: Linear Least Squares (batch)

Includes:

• Parameter estimation example
• Linear least squares
• Least squares connection to statistics

Week 2: Minimum Variance

Includes:

• Linear sequential estimation
• Random variables, covariance
• Minimum variance estimation
• Cramer Rao

Week 3: Full order and Kalman filter

Includes:

• Planar drone example
• Linearization example
• Discrete linear Kalman filter