A symmetric, positive definite square matrix A has a Cholesky decomposition into a product of a lower triangular matrix L and its transpose L^T. This is sometimes referred to as taking the square-root of a matrix. The Cholesky decomposition can only be carried out when all the eigenvalues of the matrix are positive. This decomposition can be used to convert the linear system A x = b into a pair of triangular systems L y = b, L^T x = y, which can be solved by forward and back-substitution.
GSL::Linalg::Complex::Cholesky::decomp(A)
GSL::Linalg::Complex::cholesky_decomp(A)
GSL::EDOM
. GSL::Linalg::Complex::Cholesky::solve(chol, b, x)
GSL::Linalg::Complex::cholesky_solve(chol, b, x)
GSL::Linalg::Complex::Cholesky::decomp
.GSL::Linalg::Complex::Cholesky::svx(chol, x)
GSL::Linalg::Complex::cholesky_svx(chol, x)
GSL::Linalg::Complex::Cholesky::decomp
. On input x
should contain the right-hand side b,
which is replaced by the solution on output.