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annotate matrixcomp/augment.m @ 0:8f23314345f4 draft
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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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Create local repository for matrix toolboxes. Step #0 done.
Antonio Pino Robles <data.script93@gmail.com>
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1 function C = augment(A, alpha) |
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2 %AUGMENT Augmented system matrix. |
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3 % AUGMENT(A, ALPHA) is the square matrix |
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4 % [ALPHA*EYE(m) A; A' ZEROS(n)] of dimension m+n, where A is m-by-n. |
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5 % It is the symmetric and indefinite coefficient matrix of the |
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6 % augmented system associated with a least squares problem |
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7 % minimize NORM(A*x-b). ALPHA defaults to 1. |
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8 % Special case: if A is a scalar, n say, then AUGMENT(A) is the |
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9 % same as AUGMENT(RANDN(p,q)) where n = p+q and |
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10 % p = ROUND(n/2), that is, a random augmented matrix |
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11 % of dimension n is produced. |
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12 % The eigenvalues of AUGMENT(A,ALPHA) are given in terms of the |
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13 % singular values s(i) of A (where m>n) by |
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14 % ALPHA/2 +/- SQRT( s(i)^2*ALPHA^2 + 1/4 ), i=1:n (2n eigenvalues), |
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15 % ALPHA, (m-n eigenvalues). |
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16 % If m < n then the first expression provides 2m eigenvalues and the |
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17 % remaining n-m eigenvalues are zero. |
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18 % |
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19 % See also SPAUGMENT. |
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20 |
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21 % References: |
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22 % G. H. Golub and C. F. Van Loan, Matrix Computations, third |
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23 % Edition, Johns Hopkins University Press, Baltimore, Maryland, |
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24 % 1996; sec. 5.6.4. |
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25 % N. J. Higham, Accuracy and Stability of Numerical Algorithms, |
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26 % Second edition, Society for Industrial and Applied Mathematics, |
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27 % Philadelphia, PA, 2002; sec. 20.5. |
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28 |
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29 [m, n] = size(A); |
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30 if nargin < 2, alpha = 1; end |
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31 |
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32 if max(m,n) == 1 |
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33 n = A; |
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34 p = round(n/2); |
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35 q = n - p; |
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36 A = randn(p,q); |
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37 m = p; n = q; |
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38 end |
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39 |
8f23314345f4
Create local repository for matrix toolboxes. Step #0 done.
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parents:
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40 C = [alpha*eye(m) A; A' zeros(n)]; |