Lecture 18: Sensitivity Of Linear Equations To Data Error
author: Stephen P. Boyd,
Department of Electrical Engineering, Stanford University
published: May 31, 2010, recorded: September 2007, views: 2632
released under terms of: Creative Commons Attribution Non-Commercial (CC-BY-NC)
published: May 31, 2010, recorded: September 2007, views: 2632
released under terms of: Creative Commons Attribution Non-Commercial (CC-BY-NC)
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Getting closer. Well, we'll just not worry about it. It's still twisted, but that's okay. So we'll look at what happens when Y varies. Of course, if Y varies a little bit, then X will vary a little bit, and the change in X will be A inverse delta Y. Last time, I think, I pointed this out, but if you have a matrix, which is invertible, nonsingular, but where the inverse is huge – and of course this is exactly what you'd get if you had a matrix which was, for example, singular, and then you perturbed it slightly to make it nonsingular. You will have a matrix that's now nonsingular, but it’s inverse if going to be huge. ...
See the whole transcript at Introduction to Linear Dynamical Systems - Lecture 18
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