SVD and Optimal Truncation

This video describes how to truncate the singular value decomposition (SVD) for matrix approximation. See paper by Gavish and Donoho "The Optimal Hard Threshold for Singular Values is 4/\sqrt{3}" https://arxiv.org/abs/1305.5870 https://ieeexplore.ieee.org/document/6846297  These lectures follow Chapter 1 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/ Book Website: http://databookuw.com Book PDF: http://databookuw.com/databook.pdf Brunton Website: eigensteve.com This video was produced at the University of Washington