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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