Home > gmmbayestb-v1.0 > gmmb_weightprior.m

gmmb_weightprior

PURPOSE ^

GMMB_WEIGHTPRIOR Multiply PDF values with constant priors

SYNOPSIS ^

function p = gmmb_weightprior(pdfmat, bayesS);

DESCRIPTION ^

GMMB_WEIGHTPRIOR   Multiply PDF values with constant priors

     P = GMMB_WEIGHTPRIOR(pdfmat, bayesS)

     pdfmat = N x K matrix of PDF values at N points
              in K different PDFs (the output of gmmb_pdf)
     bayesS = the bayesS struct used to compute pdfmat,
              used fields: apriories
     P = N x K matrix of weighted PDF values.

     See also GMMB_PDF.


 Author(s):
    Pekka Paalanen <pekka.paalanen@lut.fi>

 Copyright:

   Bayesian Classifier with Gaussian Mixture Model Pdf
   functionality is Copyright (C) 2003, 2004 by Pekka Paalanen and
   Joni-Kristian Kamarainen.

   $Name:  $ $Revision: 1.1 $  $Date: 2004/11/02 08:32:22 $

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 %GMMB_WEIGHTPRIOR   Multiply PDF values with constant priors
0002 %
0003 %     P = GMMB_WEIGHTPRIOR(pdfmat, bayesS)
0004 %
0005 %     pdfmat = N x K matrix of PDF values at N points
0006 %              in K different PDFs (the output of gmmb_pdf)
0007 %     bayesS = the bayesS struct used to compute pdfmat,
0008 %              used fields: apriories
0009 %     P = N x K matrix of weighted PDF values.
0010 %
0011 %     See also GMMB_PDF.
0012 %
0013 %
0014 % Author(s):
0015 %    Pekka Paalanen <pekka.paalanen@lut.fi>
0016 %
0017 % Copyright:
0018 %
0019 %   Bayesian Classifier with Gaussian Mixture Model Pdf
0020 %   functionality is Copyright (C) 2003, 2004 by Pekka Paalanen and
0021 %   Joni-Kristian Kamarainen.
0022 %
0023 %   $Name:  $ $Revision: 1.1 $  $Date: 2004/11/02 08:32:22 $
0024 %
0025 
0026 function p = gmmb_weightprior(pdfmat, bayesS);
0027 
0028 N = size(pdfmat, 1);
0029 priors = [bayesS.apriories];
0030 
0031 p = pdfmat .* repmat(priors, N, 1);

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