DynCont#1: SVD, Knuth you tube lecture video

1.  Singular value decomposition exists for all rectangular matrices
2. A square is a rectangle
3. LR , LQR, LU may not exist for some matrices
4. All matrices are basically rotation and stretching.
5. A = ULV'
6. U and V are rotations
7. L is the scaling 
8. L square will have the eigen values of AA'
9. U and V are orthonormal matrices, so their inverse and transpose are same
   
10.