ccl_learnv_pred_ncl

 Unp = ccl_learnv_pred_ncl ( model, X )

 Predict null space components using learnt model

 Input:

   model                       Learnt model parameters
   X                           Input state variable

 Output:

   Unp                          Null space component prediction

0001 function Unp = ccl_learnv_pred_ncl ( model, X )
0002 % Unp = ccl_learnv_pred_ncl ( model, X )
0003 %
0004 % Predict null space components using learnt model
0005 %
0006 % Input:
0007 %
0008 %   model                       Learnt model parameters
0009 %   X                           Input state variable
0010 %
0011 % Output:
0012 %
0013 %   Unp                          Null space component prediction
0014 
0015 
0016 
0017 
0018 % CCL: A MATLAB library for Constraint Consistent Learning
0019 % Copyright (C) 2007  Matthew Howard
0020 % Contact: matthew.j.howard@kcl.ac.uk
0021 %
0022 % This library is free software; you can redistribute it and/or
0023 % modify it under the terms of the GNU Lesser General Public
0024 % License as published by the Free Software Foundation; either
0025 % version 2.1 of the License, or (at your option) any later version.
0026 %
0027 % This library is distributed in the hope that it will be useful,
0028 % but WITHOUT ANY WARRANTY; without even the implied warranty of
0029 % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
0030 % Lesser General Public License for more details.
0031 %
0032 % You should have received a copy of the GNU Library General Public
0033 % License along with this library; if not, write to the Free
0034 % Software Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
0035 
0036 dim_N = size( X, 2 );
0037 dim_U = size( model.w, 1 );
0038 Unp   = zeros(dim_U, dim_N );
0039 for i = 1 : dim_N
0040     Unp(:,i) = model.w * model.phi( X(:,i) );
0041 end
0042 end