Mercurial > hg > camir-aes2014
comparison toolboxes/FullBNT-1.0.7/netlab3.3/gsamp.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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-1:000000000000 | 0:e9a9cd732c1e |
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1 function x = gsamp(mu, covar, nsamp) | |
2 %GSAMP Sample from a Gaussian distribution. | |
3 % | |
4 % Description | |
5 % | |
6 % X = GSAMP(MU, COVAR, NSAMP) generates a sample of size NSAMP from a | |
7 % D-dimensional Gaussian distribution. The Gaussian density has mean | |
8 % vector MU and covariance matrix COVAR, and the matrix X has NSAMP | |
9 % rows in which each row represents a D-dimensional sample vector. | |
10 % | |
11 % See also | |
12 % GAUSS, DEMGAUSS | |
13 % | |
14 | |
15 % Copyright (c) Ian T Nabney (1996-2001) | |
16 | |
17 d = size(covar, 1); | |
18 | |
19 mu = reshape(mu, 1, d); % Ensure that mu is a row vector | |
20 | |
21 [evec, eval] = eig(covar); | |
22 | |
23 deig=diag(eval); | |
24 | |
25 if (~isreal(deig)) | any(deig<0), | |
26 warning('Covariance Matrix is not OK, redefined to be positive definite'); | |
27 eval=abs(eval); | |
28 end | |
29 | |
30 coeffs = randn(nsamp, d)*sqrt(eval); | |
31 | |
32 x = ones(nsamp, 1)*mu + coeffs*evec'; |