Pages du manuel Linux : Fonctions des bibliothèques

cgbtrf
compute an LU factorization of a complex m-by-n band matrix A using partial pivoting with row interchanges
cgbtrs
solve a system of linear equations A * X = B, A**T * X = B, or A**H * X = B with a general band matrix A using the LU factorization computed by CGBTRF
cgebak
form the right or left eigenvectors of a complex general matrix by backward transformation on the computed eigenvectors of the balanced matrix output by CGEBAL
cgebal
balance a general complex matrix A
cgebd2
reduce a complex general m by n matrix A to upper or lower real bidiagonal form B by a unitary transformation
cgebrd
reduce a general complex M-by-N matrix A to upper or lower bidiagonal form B by a unitary transformation
cgecon
estimate the reciprocal of the condition number of a general complex matrix A, in either the 1-norm or the infinity-norm, using the LU factorization computed by CGETRF
cgeequ
compute row and column scalings intended to equilibrate an M-by-N matrix A and reduce its condition number
cgees
compute for an N-by-N complex nonsymmetric matrix A, the eigenvalues, the Schur form T, and, optionally, the matrix of Schur vectors Z
cgeesx
compute for an N-by-N complex nonsymmetric matrix A, the eigenvalues, the Schur form T, and, optionally, the matrix of Schur vectors Z
cgeev
compute for an N-by-N complex nonsymmetric matrix A, the eigenvalues and, optionally, the left and/or right eigenvectors
cgeevx
compute for an N-by-N complex nonsymmetric matrix A, the eigenvalues and, optionally, the left and/or right eigenvectors
cgegs
routine is deprecated and has been replaced by routine CGGES
cgegv
routine is deprecated and has been replaced by routine CGGEV
cgehd2
reduce a complex general matrix A to upper Hessenberg form H by a unitary similarity transformation
cgehrd
reduce a complex general matrix A to upper Hessenberg form H by a unitary similarity transformation
cgelq2
compute an LQ factorization of a complex m by n matrix A
cgelqf
compute an LQ factorization of a complex M-by-N matrix A
cgels
solve overdetermined or underdetermined complex linear systems involving an M-by-N matrix A, or its conjugate-transpose, using a QR or LQ factorization of A
cgelsd
compute the minimum-norm solution to a real linear least squares problem
cgelss
compute the minimum norm solution to a complex linear least squares problem
cgelsx
routine is deprecated and has been replaced by routine CGELSY
cgelsy
compute the minimum-norm solution to a complex linear least squares problem
cgemm
perform one of the matrix-matrix operations C := alpha*op( A )*op( B ) + beta*C,
cgemv
perform one of the matrix-vector operations y := alpha*A*x + beta*y, or y := alpha*A'*x + beta*y, or y := alpha*conjg( A' )*x + beta*y,
cgeql2
compute a QL factorization of a complex m by n matrix A
cgeqlf
compute a QL factorization of a complex M-by-N matrix A
cgeqp3
compute a QR factorization with column pivoting of a matrix A
cgeqpf
routine is deprecated and has been replaced by routine CGEQP3
cgeqr2
compute a QR factorization of a complex m by n matrix A
cgeqrf
compute a QR factorization of a complex M-by-N matrix A
cgerc
perform the rank 1 operation A := alpha*x*conjg( y' ) + A,
cgerfs
improve the computed solution to a system of linear equations and provides error bounds and backward error estimates for the solution
cgerq2
compute an RQ factorization of a complex m by n matrix A
cgerqf
compute an RQ factorization of a complex M-by-N matrix A
cgeru
perform the rank 1 operation A := alpha*x*y' + A,
cgesc2
solve a system of linear equations A * X = scale* RHS with a general N-by-N matrix A using the LU factorization with complete pivoting computed by CGETC2
cgesdd
compute the singular value decomposition (SVD) of a complex M-by-N matrix A, optionally computing the left and/or right singular vectors, by using divide-and-conquer method
cgesv
compute the solution to a complex system of linear equations A * X = B,
cgesvd
compute the singular value decomposition (SVD) of a complex M-by-N matrix A, optionally computing the left and/or right singular vectors
cgesvx
use the LU factorization to compute the solution to a complex system of linear equations A * X = B,
cgetc2
compute an LU factorization, using complete pivoting, of the n-by-n matrix A
cgetf2
compute an LU factorization of a general m-by-n matrix A using partial pivoting with row interchanges
cgetrf
compute an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges
cgetri
compute the inverse of a matrix using the LU factorization computed by CGETRF
cgetrs
solve a system of linear equations A * X = B, A**T * X = B, or A**H * X = B with a general N-by-N matrix A using the LU factorization computed by CGETRF
cggbak
form the right or left eigenvectors of a complex generalized eigenvalue problem A*x = lambda*B*x, by backward transformation on the computed eigenvectors of the balanced pair of matrices output by CGGBAL
cggbal
balance a pair of general complex matrices (A,B)
cgges
compute for a pair of N-by-N complex nonsymmetric matrices (A,B), the generalized eigenvalues, the generalized complex Schur form (S, T), and optionally left and/or right Schur vectors (VSL and VSR)
cggesx
compute for a pair of N-by-N complex nonsymmetric matrices (A,B), the generalized eigenvalues, the complex Schur form (S,T),