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A note on the complex semi‐definite matrix Procrustes problem
Author(s) -
Kiskiras J.,
Halikias G. D.
Publication year - 2007
Publication title -
numerical linear algebra with applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.02
H-Index - 53
eISSN - 1099-1506
pISSN - 1070-5325
DOI - 10.1002/nla.535
Subject(s) - mathematics , hermitian matrix , positive definite matrix , matrix (chemical analysis) , rank (graph theory) , convergence (economics) , mathematical optimization , numerical linear algebra , optimization problem , algorithm , parametrization (atmospheric modeling) , numerical analysis , combinatorics , pure mathematics , mathematical analysis , eigenvalues and eigenvectors , physics , materials science , quantum mechanics , economics , composite material , economic growth , radiative transfer
This note outlines an algorithm for solving the complex ‘matrix Procrustes problem’. This is a least‐squares approximation over the cone of positive semi‐definite Hermitian matrices, which has a number of applications in the areas of Optimization, Signal Processing and Control. The work generalizes the method of Allwright ( SIAM J. Control Optim . 1988; 26 (3):537–556), who obtained a numerical solution to the real‐valued version of the problem. It is shown that, subject to an appropriate rank assumption, the complex problem can be formulated in a real setting using a matrix‐dilation technique, for which the method of Allwright is applicable. However, this transformation results in an over‐parametrization of the problem and, therefore, convergence to the optimal solution is slow. Here, an alternative algorithm is developed for solving the complex problem, which exploits fully the special structure of the dilated matrix. The advantages of the modified algorithm are demonstrated via a numerical example. Copyright © 2007 John Wiley & Sons, Ltd.