Explore a gentle introduction to modeling complex time-varying systems using matrices and vectors through a probabilistic weather model. Learn how to represent weather states as vectors and update probabilities using matrix multiplication. Follow along with code examples in both Python and MATLAB as you build a simple yet insightful model for predicting weather patterns. Discover how to store and manipulate weather state probabilities, implement dynamical system update rules, and gain insights into making the model more realistic. This educational video provides a practical foundation for understanding matrix-based modeling techniques applicable to various fields beyond meteorology.
Gentle Introduction to Modeling with Matrices and Vectors - A Probabilistic Weather Model
Steve Brunton via YouTube
Overview
Syllabus
Overview
Building a simple weather model
Modeling the state as a vector
Writing the dynamical system update rule as a matrix
Matlab code example
Python code example
Teaser of how to make system more realistic
Taught by
Steve Brunton
