DynCont#2: SVD, MIT 18.065 Strang you tube lecture video
- A * v = u * Sigma
- Matrix A times an orthogonal vector matrix = another orthogonal vector matrix scaled by sigma
- Sigma is diagonal matrix
- Sigma is the square of eigen values of A A'
- AA' is symmetric and positive semi definite
- If A is mxn, AA' = m x m . Then, it will have m eigen values.
- If A is mxn, A'A = n x n . Then, it will have n eigen values. If m is greater than n, then m-n eigen values of AA' will be zero.
- Use of SVD:?
- SVD from lecture 29 in 18:06?
- Use of SVD from Knuth?
No comments:
Post a Comment