This video discusses the important problem of how to select the fewest and most informative sensors to estimate a high-dimensional data set. I will discuss the algorithm and give several examples from control theory, to insect flight, to manufacturing.
Book Website: http://databookuw.com
Book PDF: http://databookuw.com/databook.pdf
These lectures follow Chapter 3 from:
"Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Brunton and Kutz
Amazon: https://www.amazon.com/Data-Driven-Science-Engineering-Learning-Dynamical/dp/1108422098/
Brunton Website: eigensteve.com
This video was produced at the University of Washington