ARPACK
Examples of using ARPACK for Eigenvalues and Eigenvectors of Large Matrices
ARPACK
is a MATLAB library which
computes eigenvalues and eigenvectors of large matrices. The ARPACK
library is accessible in MATLAB via the EIGS command. This directory
contains some examples of how to use ARPACK for specific problems.

help eigs
will print out information about how to use the EIGS
command inside of MATLAB to interface with ARPACK.

Information about the use of the ARPACK execution
trace facilities available through "debug.h" is given in
arpack_debug.txt

Information about the use of the ARPACK operation count
and timing statistics available through "stat.h" is given in
arpack_stat.txt
Licensing:
The computer code and data files described and made available on this web page
are distributed under
the GNU LGPL license.
Languages:
ARPACK is available in
a FORTRAN90 version and
a MATLAB version.
Related Data and Programs:
EISPACK,
a FORTRAN90 library containing
eigenvalue routines.
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.
PAGERANK,
a MATLAB library which
illustrates the eigenvalue (power method) and surfer (Markov chain)
approaches to ranking web pages.
TEST_EIGEN,
a MATLAB library which
defines various eigenvalue
test cases.
TEST_MAT,
a MATLAB library which
defines various test matrices.
Reference:

Richard Lehoucq, Danny Sorensen, Chao Yang,
ARPACK User's Guide:
Solution of Large Scale Eigenvalue Problems with
Implicitly Restarted Arnoldi Methods.

Danny Sorensen,
Implicitly Restarted Arnoldi/Lanczos Methods for
Large Scale Eigenvalue Calculations.
Examples and Tests:

arpack_test.m,
a script that runs all the tests.

arpack_test_output.txt,
the output file.

arpack_test01.m,
tests EIGS for smallest and largest eigenvalues,
with the matrix supplied explicitly.

arpack_test02.m,
tests EIGS for smallest eigenvalues,
with the matrix supplied implicitly, by a routine
which computes inverse(A)*x.

ainv_x.m,
computes inverse(A)*x for problem 2.

timestamp.m,
prints the current YMDHMS date as a timestamp.
You can go up one level to
the MATLAB source codes.
Last revised on 26 February 2010.