MIMO_ML_SelectEstimParam

PURPOSE ^

SYNOPSIS ^

function TheMat = MIMO_ML_SelectEstimParam(TheMat, TheSel);

DESCRIPTION ^

 function TheMat = MIMO_ML_SelectEstimParam(TheMat, TheSel);

   selects the columns of the matrix TheMat corresponding to the estimated parameters


    Output parameter

        TheMat                =    matrix where the columns contain only the estimated model parameters
                                size: rows x number of free parameters


    Input parameter

        TheMat                =    matrix where the columns contain all model parameters
                                size: rows x number of all parameters
        TheSel                =    structure with fields 'A', 'B', 'Ig'
                                    TheSel = struct('A',[],'B',[], 'Ig', [])
                                    TheSel.A = 1 x (OrderA+1)
                                        TheSel.A(r) = 1 if coeff. a(r-1) is unknown
                                        Sel.A(r) = 0 if coeff. a(r-1) = 0
                                    TheSel.B = ny x nu x (OrderB+1)
                                        TheSel.B(i,j,r) = 1 if coeff. b(i,j,r-1) is unknown
                                        TheSel.B(i,j,r) = 0 if coeff. b(i,j,r-1) = 0
                                    TheSel.Ig = ny x (OrderIg+1)
                                        TheSel.Ig(i,r) = 1 if coeff. ig(i,r-1) is unknown
                                        TheSel.Ig(i,r) = 0 if coeff. ig(i,r-1) = 0


 Copyright (c) Rik Pintelon, Vrije Universiteit Brussel - dept. ELEC, November 2009
 All rights reserved.
 Software can be used freely for non-commercial applications only.

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function TheMat = MIMO_ML_SelectEstimParam(TheMat, TheSel);
0002 %
0003 % function TheMat = MIMO_ML_SelectEstimParam(TheMat, TheSel);
0004 %
0005 %   selects the columns of the matrix TheMat corresponding to the estimated parameters
0006 %
0007 %
0008 %    Output parameter
0009 %
0010 %        TheMat                =    matrix where the columns contain only the estimated model parameters
0011 %                                size: rows x number of free parameters
0012 %
0013 %
0014 %    Input parameter
0015 %
0016 %        TheMat                =    matrix where the columns contain all model parameters
0017 %                                size: rows x number of all parameters
0018 %        TheSel                =    structure with fields 'A', 'B', 'Ig'
0019 %                                    TheSel = struct('A',[],'B',[], 'Ig', [])
0020 %                                    TheSel.A = 1 x (OrderA+1)
0021 %                                        TheSel.A(r) = 1 if coeff. a(r-1) is unknown
0022 %                                        Sel.A(r) = 0 if coeff. a(r-1) = 0
0023 %                                    TheSel.B = ny x nu x (OrderB+1)
0024 %                                        TheSel.B(i,j,r) = 1 if coeff. b(i,j,r-1) is unknown
0025 %                                        TheSel.B(i,j,r) = 0 if coeff. b(i,j,r-1) = 0
0026 %                                    TheSel.Ig = ny x (OrderIg+1)
0027 %                                        TheSel.Ig(i,r) = 1 if coeff. ig(i,r-1) is unknown
0028 %                                        TheSel.Ig(i,r) = 0 if coeff. ig(i,r-1) = 0
0029 %
0030 %
0031 % Copyright (c) Rik Pintelon, Vrije Universiteit Brussel - dept. ELEC, November 2009
0032 % All rights reserved.
0033 % Software can be used freely for non-commercial applications only.
0034 %
0035 
0036 
0037 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0038 % create row vector that selects the columns of the %
0039 % matrix corresponding to the estimated parameters  %
0040 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0041 
0042 % A polynomial
0043 Select = TheSel.A;
0044 
0045 % B ny x nu matrix polynomial
0046 % for jj = 1:nu
0047 %     for ii = 1:ny
0048 %         Select = [Select, squeeze(TheSel.B(ii,jj,:)).'];
0049 %     end % ii
0050 % end % jj
0051 SelB = permute(TheSel.B,[3,1,2]);
0052 Select = [Select, SelB(:).'];
0053 
0054 % Ig ny x 1 vector polynomial
0055 % for ii = 1:ny
0056 %     Select = [Select, TheSel.Ig(ii,:)];
0057 % end % ii
0058 SelIg = TheSel.Ig.';
0059 Select = [Select, SelIg(:).'];
0060 
0061 
0062 %%%%%%%%%%%%%%%%%%%%%%%%%%%
0063 % selection columns Jacob %
0064 %%%%%%%%%%%%%%%%%%%%%%%%%%%
0065 
0066 TheMat = TheMat(:, Select == 1);

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