See: Description
| Class | Description |
|---|---|
| SparseDComplexCholeskyDecomposition |
For a symmetric, positive definite matrix A, the Cholesky
decomposition is a lower triangular matrix L so that A = L*L'; If
the matrix is not symmetric positive definite, the IllegalArgumentException
is thrown.
|
| SparseDComplexLUDecomposition |
For a square matrix A, the LU decomposition is an unit lower
triangular matrix L, an upper triangular matrix U, and a
permutation vector piv so that A(piv,:) = L*U
|
| SparseDComplexQRDecomposition |
For an m x n matrix A with m >= n, the QR
decomposition is an m x n orthogonal matrix Q and an
n x n upper triangular matrix R so that A = Q*R.
|
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