TEST_EIGEN is a MATLAB library which generates eigenvalue tests.
The current version of the code can only generate a symmetric or nonsymmetric matrix of arbitrary size, with eigenvalues distributed according to a normal distribution whose mean and standard deviation are specified by the user (subroutines R8SYMM_GEN and R8NSYMM_GEN).
The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.
TEST_EIGEN is available in a C version and a C++ version and a FORTRAN90 version and a MATLAB version and a Python version.
ARPACK, MATLAB programs which illustrate the use of the ARPACK libraruy to compute eigenvalues of large matrices.
EISPACK, a FORTRAN90 library which carries out eigenvalue computations; superseded by LAPACK;
JACOBI_EIGENVALUE, a MATLAB library which implements the Jacobi iteration for the iterative determination of the eigenvalues and eigenvectors of a real symmetric matrix.
LAPACK_EXAMPLES, a FORTRAN90 program which demonstrates the use of the LAPACK linear algebra library.
POWER_METHOD, a MATLAB library which carries out the power method for finding a dominant eigenvalue and its eigenvector.
TEST_MAT, a MATLAB library which defines test matrices.
TOMS343,
a FORTRAN77 library which
computes the eigenvalues and
eigenvectors of a general real matrix;
this is a FORTRAN77 version of ACM TOMS algorithm 343.
TOMS384,
a FORTRAN77 library which
computes the eigenvalues and eigenvectors
of a symmetric matrix;
this is a FORTRAN77 version of ACM TOMS algorithm 384.
You can go up one level to the MATLAB source codes.