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)
Categories

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

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

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: