JACOBI_EIGENVALUE
Eigenvalues and Eigenvectors of a Symmetric Matrix


JACOBI_EIGENVALUE is a MATLAB library which computes the eigenvalues and eigenvectors of a real symmetric matrix.

Given a real symmetric NxN matrix A, JACOBI_EIGENVALUE carries out an iterative procedure known as Jacobi's iteration, to determine a N-vector D of real, positive eigenvalues, and an NxN matrix V whose columns are the corresponding eigenvectors, so that, for each column J of the eigenmatrix:

        A * Vj = Dj * Vj
      

Licensing:

The computer code and data files made available on this web page are distributed under the GNU LGPL license.

Languages:

JACOBI_EIGENVALUE is available in a C version and a C++ version and a FORTRAN77 version and a FORTRAN90 version and a MATLAB version and a Python version.

Related Data and Programs:

ARPACK, a MATLAB library which uses Arnoldi methods to compute some eigenvalues and eigenvectors of matrices, which may be very large.

TEST_EIGEN, a MATLAB library which implements test matrices for eigenvalue analysis.

TEST_MAT, a MATLAB library which defines test matrices, some of which have known determinants, eigenvalues and eigenvectors, inverses and so on.

Reference:

  1. Gene Golub, Charles VanLoan,
    Matrix Computations, Third Edition,
    Johns Hopkins, 1996,
    ISBN: 0-8018-4513-X,
    LC: QA188.G65.

Source Code:

Examples and Tests:

You can go up one level to the MATLAB source codes.


Last revised on 14 July 2013.