Numerical Linear Algebra
1. Vectors, matrices, norms.
2. Orthogonal factorizations:
Singular Value Decomposition
QR factorization
Gram-Schmidt orthogonalization
Householder reflectors
2. Least squares problems:
Orthogonal projections
Moore-Penroose pseudoinverse
3. Machine arithmetics, floating point representation
4. Stability and conditioning of problems
5. Gaussian elimination
6. Eigenvalue problems
Reduction to Hessenberg form
Power, inverse power and Rayleigh quotient iterations
Simultaneous iterations and QR algorithm
