Mercurial > matrix-functions
view matrixcomp/augment.m @ 0:8f23314345f4 draft
Create local repository for matrix toolboxes. Step #0 done.
author | Antonio Pino Robles <data.script93@gmail.com> |
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date | Wed, 06 May 2015 14:56:53 +0200 |
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function C = augment(A, alpha) %AUGMENT Augmented system matrix. % AUGMENT(A, ALPHA) is the square matrix % [ALPHA*EYE(m) A; A' ZEROS(n)] of dimension m+n, where A is m-by-n. % It is the symmetric and indefinite coefficient matrix of the % augmented system associated with a least squares problem % minimize NORM(A*x-b). ALPHA defaults to 1. % Special case: if A is a scalar, n say, then AUGMENT(A) is the % same as AUGMENT(RANDN(p,q)) where n = p+q and % p = ROUND(n/2), that is, a random augmented matrix % of dimension n is produced. % The eigenvalues of AUGMENT(A,ALPHA) are given in terms of the % singular values s(i) of A (where m>n) by % ALPHA/2 +/- SQRT( s(i)^2*ALPHA^2 + 1/4 ), i=1:n (2n eigenvalues), % ALPHA, (m-n eigenvalues). % If m < n then the first expression provides 2m eigenvalues and the % remaining n-m eigenvalues are zero. % % See also SPAUGMENT. % References: % G. H. Golub and C. F. Van Loan, Matrix Computations, third % Edition, Johns Hopkins University Press, Baltimore, Maryland, % 1996; sec. 5.6.4. % N. J. Higham, Accuracy and Stability of Numerical Algorithms, % Second edition, Society for Industrial and Applied Mathematics, % Philadelphia, PA, 2002; sec. 20.5. [m, n] = size(A); if nargin < 2, alpha = 1; end if max(m,n) == 1 n = A; p = round(n/2); q = n - p; A = randn(p,q); m = p; n = q; end C = [alpha*eye(m) A; A' zeros(n)];