# Linear Algebra

- vector
- vector space
- various matrix representations:
- bi-diagonal
- diagonal
- tri-diagonal
- Givens
- Hilbert
- lower/upper triangular
- permutation

- sparse vector representations:
- sparse matrix representations:
- CSR
- DOK
- LIL

- iterative sparse matrix solver:
- stationary
- Jacobi
- Gauss-Seidel
- SOR
- SSOR

- non-stationary
- Steepest Descent
- BiCG
- BiCGStabl
- CGNE
- CGNR
- CG
- CGS
- GCR
- GMRES
- MinRes
- QMR

- pre-conditioner support
- Jacobi
- SSOR
- customized

- stationary
- matrix elementary operations
- Householder transformation
- matrix inverse
- matrix measures:
- determinant
- rank
- trace
- max
- min

- power of matrix
- matrix pseudoinverse
- matrix bi-diagonalization
- matrix tri-diagonalization
- Cholesky decomposition
- Doolittle factorization
- Eigen factorization
- Gauss-Jordan elimination
- SVD factorization (for asymmetric matrix)
- Gram-Schmidt factorization
- Hessenberg factorization
- LDL decomposition
- LU decomposition
- QR decomposition

Very helpful, I've needed this explanation for 15 years!