1 | function [aMix] = soptim(aMix, aMixu, ufc, nstep, chis) |
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2 | % soptim performs simultaneous advisory design for normal mixture |
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3 | % |
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4 | % [aMix] = soptim(aMix, aMixu, ufc, nstep, chis) |
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5 | % [aMix] = soptim(aMix, aMixu, ufc, nstep) chis = 1 |
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6 | % [aMix] = soptim(aMix, aMixu, ufc) nstep = [200, 1] |
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7 | % |
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8 | % aMix : advised mixture of the type ARX LS enriched on following control states: |
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9 | % strc : common control structure |
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10 | % ufc : normalised vector qualifying components: |
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11 | % dangerous component (0), not dangerous (positive number) |
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12 | % kc : lift of quadratic forms |
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13 | % UDc : cell vector of u'du decompositions of KLD kernels |
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14 | % udca : u'du decomposition of average KLD kernel in UDc |
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15 | % kca : average lift of quadratic forms kc |
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16 | % aMixu : desired mixture (user's target) of the type ARX LS with control states |
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17 | % ufc : vector qualifying components: 0 - dangerous component, (1) - not |
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18 | % nstep : parameters [ns1,per] determining design horizon, i.e. horizon = ns1*per; |
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19 | % ns1 : number of block repetition |
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20 | % per : horizon of a block |
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21 | % if nstep is defined by parameter nsl only then per is set to 1 |
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22 | % chis : indicates strategy chosen: chis=1 for receding horizon (default) and chis=-1 for IST |
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23 | % |
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24 | % Design : J. Bohm |
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25 | % Updated : June, 2002 |
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26 | % Project : ProDaCTools, IST-1999-12058 |
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27 | % See also : udupdt, getdvect, facchng, facarxls |
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28 | |
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29 | % References : \ref{ch9} |
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30 | % Note : |
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31 | % Updated : |
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32 | |
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33 | |
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34 | if (nargin < 3) | ~any(ufc)error(sprintf('%s\n%s\n%s','ufc was not correcly set, define it as a vector','of a length "ncom" having at least one nonzero element ','or use a function ufcgen')) ;end |
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35 | |
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36 | if (nargin <4), nstep=[200,1];chis=1;end |
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37 | if (nargin <5), chis=1;end |
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38 | |
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39 | if(isempty(aMix.states.uchn)) error('uoptim needs nonempty list of channels with recognisable actions'); end; |
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40 | % normalisation of ufc |
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41 | ufc = ufc/sum(ufc); |
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42 | |
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43 | %Inititialization |
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44 | ncom = length(aMix.dfcs); |
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45 | dfcs = aMix.dfcs; |
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46 | strc = aMix.states.strc; % common control structure |
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47 | nPsi = max(size(strc)); % length of regression vector + data |
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48 | pochn = aMix.states.pochn; % list of channels with o-innovations |
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49 | npochn = length(pochn); % number of channels with o-innovations |
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50 | nychn = length(aMix.states.modelled); % number of modelled channels |
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51 | nouts = length(aMix.states.outs); % number of innovation channels |
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52 | npsi = nPsi-nychn; % length of the regression vector |
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53 | kc0 = aMixu.states.kc; |
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54 | udca = aMixu.states.udca; |
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55 | kca = aMixu.states.kca; |
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56 | coms = aMix.coms; |
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57 | Ethz = zeros(1,nPsi); |
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58 | UDc = aMixu.states.UDc; |
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59 | lss = length(nstep); |
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60 | lrica = zeros(1,nPsi-1); |
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61 | %test of aMixu |
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62 | coves=zeros(1,npochn); |
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63 | % if npochn~=length(aMixu.Facs),error('aMixu not correctly set'); end |
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64 | for i=1:npochn, |
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65 | coves(i)=aMixu.Facs{i}.cove; |
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66 | end |
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67 | if ~any(coves), error('aMixu not correctly set, Facs{.}.cove must be >0'),end |
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68 | |
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69 | for i=1:ncom, % cycle over number of components ncom |
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70 | Ric{i}= zeros(nPsi); % KLD kernels |
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71 | kcc(i)=0; % lift of quadratic forms |
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72 | end |
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73 | df=dfcs/sum(dfcs); |
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74 | % setting of design horizon |
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75 | if lss==2 |
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76 | steps = nstep(1)*nstep(2); per=nstep(2); |
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77 | else |
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78 | steps = nstep; per=1; |
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79 | end |
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80 | if chis>0, % if the strategy starts from zero |
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81 | udca = zeros(nPsi); kca =0; |
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82 | end |
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83 | %Main design cycle, iterations over the horizon of the criterion |
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84 | for iter=1:steps, % ===================== iterations till design horizon |
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85 | % ricmn is an auxiliary array accumulating results of optimization |
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86 | if mod(iter-1,per)==0, |
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87 | % shift of a matrix from bottom right to top left by nychn |
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88 | % if nPsi>nychn+1 |
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89 | [udca, lrica]= ricshift(udca,lrica,nychn,nPsi,npsi); |
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90 | % end %if nPsi |
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91 | udca(nPsi,nPsi)= 0; |
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92 | end %if mod |
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93 | |
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94 | for i=1:ncom % ......................... cycle over all components |
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95 | if mod(iter-1,per)==0, |
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96 | % if ufc(i)==0, kcc(i)=1e30; continue; end % excluding bad components |
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97 | ric = udca; % ric is auxiliarry working array |
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98 | lric(i,:)=lrica; |
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99 | kcc(i) = -npochn +kc0(i); |
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100 | % adding to each component its stationary loss |
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101 | for j=1:npsi, % |
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102 | red=UDc{i}(j,:); |
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103 | red(j)=1; |
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104 | ric= udupdt(ric,red,ufc(i)*UDc{i}(j,j)); |
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105 | end % for j |
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106 | else |
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107 | % iteration continues in corresponding component kernel and lift |
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108 | % shift of a matrix from bottom right to top left by nychn |
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109 | if nPsi>nychn+1, |
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110 | [ric,lric(i,:)]=ricshift(Ric{i},lric(i,:),nychn,nPsi,npsi); |
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111 | end % if nPsi |
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112 | ric(nPsi,nPsi) = Ric{i}(nPsi,nPsi); |
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113 | end %if mod |
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114 | % expectation is calculated channel by channel |
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115 | for j=1: nouts %--------------------- cycle over innovation channels |
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116 | indv = ~isempty(find(strc(1,j)==pochn)); % indicator if the channel is o-innovation |
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117 | [ric,lric,kcc]= ricexp(ric,lric,kcc,i,j,aMix,nPsi); |
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118 | % the penalization is used |
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119 | if indv, % visibility indicator |
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120 | [ric,lric,kcc]= ricpen(ric,lric,kcc,i,j,aMix,aMixu,nPsi); |
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121 | end %end if indv |
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122 | end % ------------------------------ reduced all factors of i-th component |
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123 | % now penalization |
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124 | for j=nouts+1: nychn, |
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125 | [ric,lric,kcc]= ricpenu(ric,lric,kcc,i,j,aMix,aMixu,nPsi); |
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126 | % if ric(j,j)>eps, |
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127 | % kcc(i)=kcc(i)-lric(i,j)*lric(i,j)/ric(j,j)/4; |
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128 | % disp('pred m'); |
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129 | % keyboard |
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130 | % % lric(i,:)=lric(i,:)-lric(i,j)*[zeros(1,j) ric(j,j+1:end-1)]; |
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131 | % disp('po m'); |
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132 | % keyboard |
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133 | % end % if |
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134 | end %end for |
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135 | |
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136 | [l,d]= ld2ld(ric(nouts+1: nychn,nouts+1: nychn)); |
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137 | lric(i,nychn+1:end)=lric(i,nychn+1:end)-lric(i,nouts+1: nychn)*inv(l)*ric(nouts+1: nychn,nychn+1:end-1); |
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138 | Ric{i} = ric; |
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139 | end % ...................... done for all components |
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140 | % now putting losses together |
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141 | if mod(iter,per)==0, |
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142 | udca=zeros(size(ric)); |
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143 | lrica = zeros(1,nPsi-1); |
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144 | det=ones(1,ncom); |
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145 | %%putting it together |
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146 | for i=1:ncom, |
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147 | % if ufc(i)==0, continue; end |
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148 | for j=nouts+1:nPsi, |
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149 | red = Ric{i}(j,:); |
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150 | red(j) = 1; |
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151 | udca = udupdt(udca,red,df(i)*Ric{i}(j,j)); |
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152 | end % over j |
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153 | lrica=lrica+df(i)*lric(i,:); |
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154 | |
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155 | end % over components |
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156 | end %if |
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157 | |
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158 | end % iterations |
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159 | %recalculating lric into the triangular matrix |
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160 | % for i=1:ncom % ......................... cycle over all components |
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161 | % ric=Ric{i}; |
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162 | [r,d]=ld2ld(udca); |
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163 | pom=lrica'; |
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164 | xx=zeros(nPsi -1,1); |
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165 | if d(nouts+1,nouts+1)>eps, xx(nouts+1)=pom(nouts+1)/d(nouts+1,nouts+1)/2; |
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166 | else xx(nouts+1)=0; |
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167 | end |
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168 | for j=nouts+2:nPsi-1, |
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169 | ff=r(nouts+1:end-1,j)'*d(nouts+1:end-1,nouts+1:end-1)*2*xx(nouts+1:end); |
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170 | if d(j,j)>eps,xx(j)=(pom(j)-ff)/2/d(j,j); |
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171 | else xx(j)=0; |
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172 | end |
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173 | end |
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174 | udca(:,end)= [xx ;0]; |
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175 | % end |
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176 | |
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177 | %puting calculated control factors into a mixture |
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178 | for i=1:ncom, |
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179 | % cl= Ric{i}(nouts+1:nychn,:); |
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180 | for j= nouts+1:nychn, |
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181 | jj=aMix.states.strc(1,j); |
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182 | Fac=facarxls(jj,strc(:,j+1:end)); |
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183 | Fac.Eth=-udca(j,j+1:end); |
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184 | if udca(j,j)<eps, error('synthesis uoptim uncorrect, check its input parameters'),end |
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185 | Fac.cove=1/udca(j,j); |
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186 | aMix=facchng(aMix,i,Fac); |
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187 | end |
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188 | end |
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189 | aMix.states.udca = udca; |
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190 | aMix.states.kca = kca; |
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191 | aMix.states.UDc = Ric; |
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192 | aMix.states.kc = kcc; |
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193 | |
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