acdc
所属分类:matlab编程
开发工具:matlab
文件大小:12KB
下载次数:156
上传日期:2006-07-01 13:52:01
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说明: 联合对角化方法,用于对多个矩阵同时进行联合对角化,主要用处是盲源分离。
(joint diagonalization method for the same time on a number of joint matrix diagonalization, the main use is Blind Source Separation.)
文件列表:
acdc\callacdc_sym.m (899, 2004-03-01)
acdc\acdc_sym.m (9331, 2004-03-01)
acdc\callacdc.m (1630, 2004-03-02)
acdc\acdc.m (9093, 2004-03-01)
acdc\init4acdc.m (6074, 2000-06-28)
acdc (0, 2005-12-29)
readme.txt
As of now (2-mar-04) this directory
contains the following:
* The acdc algorithm for finding the
approximate general (non-orthogonal)
joint diagonalizer (in the direct Least
Squares sense) of a set of Hermitian
matrices.
[acdc.m]
* The acdc algorithm for finding the
same for a set of Symmetric (rather than
Hermitean) matrices.
[acdc_sym.m]
Note that for real-valued matrices the
Hermitian and Symmetric cases are similar;
however, in such cases the Hermitian version
[acdc.m], rather than the Symmetric version
[acdc_sym] is preferable.
* A function that finds an initial guess
for acdc by applying hard-whitening
followed by Cardoso's orthogonal joint
diagonalizer. Note that acdc may also
be called without an initial guess,
in which case the initial guess is set
by default to the identity matrix.
The m-file includes the joint_diag
function (by Cardoso) for performing
the orthogonal part.
[init4acdc.m]
* A small routine that demonstrates the
call (with and without initialization)
to the Hermitian vesion after generating
a set of target-matrices.
[callacdc.m]
* A small routine that demonstrates the
same with the Hermitian vesion.
[callacdc_sym.m]
* The acdc and acdc_sym codes have been revised
(relative to the older version) in two aspects:
+ The overcomplete case (A has more rows than
columns) has been made explicitly available,
by introducing a new (optional) input parameter,
Nc (the number of columns in A);
+ A threshold parameter (Tol) was added as another
(optional) input parameter, to serve as a user-
defined stopping criterion. If Tol is not
specified, then an automatic threshold is used,
but a warning message is generated if the scales
of some matrices appear incompatible with
this threshold.
Contibuted By:
Dr. Arie Yeredor,
School of Electrical Engineering,
Tel-Aviv University.
e-mail: arie@eng.tau.ac.il
web-site: www.eng.tau.ac.il\~arie
comments, bug reports, questions
and suggestions are welcome.
References:
[1] Yeredor, A., Approximate Joint
Diagonalization Using Non-Orthogonal
Matrices, Proceedings of ICA2000,
pp.33-38, Helsinki, June 2000.
[2] Yeredor, A., Non-Orthogonal Joint
Diagonalization in the Least-Squares
Sense with Application in Blind Source
Separation, IEEE Trans. On Signal Processing,
vol. 50 no. 7 pp. 1545-1553, July 2002.
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