Mercurial > hg > camir-aes2014
comparison toolboxes/FullBNT-1.0.7/netlab3.3/gpcovar.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 [cov, covf] = gpcovar(net, x) | |
2 %GPCOVAR Calculate the covariance for a Gaussian Process. | |
3 % | |
4 % Description | |
5 % | |
6 % COV = GPCOVAR(NET, X) takes a Gaussian Process data structure NET | |
7 % together with a matrix X of input vectors, and computes the | |
8 % covariance matrix COV. The inverse of this matrix is used when | |
9 % calculating the mean and variance of the predictions made by NET. | |
10 % | |
11 % [COV, COVF] = GPCOVAR(NET, X) also generates the covariance matrix | |
12 % due to the covariance function specified by NET.COVARFN as calculated | |
13 % by GPCOVARF. | |
14 % | |
15 % See also | |
16 % GP, GPPAK, GPUNPAK, GPCOVARP, GPCOVARF, GPFWD, GPERR, GPGRAD | |
17 % | |
18 | |
19 % Copyright (c) Ian T Nabney (1996-2001) | |
20 | |
21 % Check arguments for consistency | |
22 errstring = consist(net, 'gp', x); | |
23 if ~isempty(errstring); | |
24 error(errstring); | |
25 end | |
26 | |
27 ndata = size(x, 1); | |
28 | |
29 % Compute prior covariance | |
30 if nargout >= 2 | |
31 [covp, covf] = gpcovarp(net, x, x); | |
32 else | |
33 covp = gpcovarp(net, x, x); | |
34 end | |
35 | |
36 % Add output noise variance | |
37 cov = covp + (net.min_noise + exp(net.noise))*eye(ndata); | |
38 |