درخواست راهنمایی

[azadmnesh]

M=csvread('C:\Documents and Settings\mina\Desktop\dat\Arial.dat&#039
چندتا حرف را با چند فونت نوشتییم وباید به تبدیل شود تا قابل اجرا باشد چه جوری این کار را باید بکنمdat تبدیل به




%in the name of the most High


input1=csvread('C:\Documents and Settings\Hamed\Desktop\fooontha\dat\Arial.dat'
input2=csvread('C:\Documents and Settings\Hamed\Desktop\fooontha\dat\bmitra.dat&#03 9;
input3=csvread('C:\Documents and Settings\Hamed\Desktop\fooontha\dat\nazanin.dat&#0 39;
input4=csvread('C:\Documents and Settings\Hamed\Desktop\fooontha\dat\zar.dat'
input5=csvread('C:\Documents and Settings\Hamed\Desktop\fooontha\dat\TAHOMA.dat&#03 9;
input6=csvread('C:\Documents and Settings\Hamed\Desktop\fooontha\dat\times.dat'
input7=csvread('C:\Documents and Settings\Hamed\Desktop\fooontha\dat\font6.dat'
input8=csvread('C:\Documents and Settings\Hamed\Desktop\fooontha\dat\font7.dat'

out=input1(:,16);
mat=input1;
in1=[mat(:,1),mat(:,2),mat(:,3),mat(:,4),mat(:,5),mat(: ,6),mat(:,7),mat(:,8),mat(:,9),mat(:,10),mat(:,11) ,mat(:,12),mat(:,13),mat(:,14),mat(:,15)];
mat=input2;
in2=[mat(:,1),mat(:,2),mat(:,3),mat(:,4),mat(:,5),mat(: ,6),mat(:,7),mat(:,8),mat(:,9),mat(:,10),mat(:,11) ,mat(:,12),mat(:,13),mat(:,14),mat(:,15)];
mat=input3;
in3=[mat(:,1),mat(:,2),mat(:,3),mat(:,4),mat(:,5),mat(: ,6),mat(:,7),mat(:,8),mat(:,9),mat(:,10),mat(:,11) ,mat(:,12),mat(:,13),mat(:,14),mat(:,15)];
mat=input4;
in4=[mat(:,1),mat(:,2),mat(:,3),mat(:,4),mat(:,5),mat(: ,6),mat(:,7),mat(:,8),mat(:,9),mat(:,10),mat(:,11) ,mat(:,12),mat(:,13),mat(:,14),mat(:,15)];
mat=input5;
in5=[mat(:,1),mat(:,2),mat(:,3),mat(:,4),mat(:,5),mat(: ,6),mat(:,7),mat(:,8),mat(:,9),mat(:,10),mat(:,11) ,mat(:,12),mat(:,13),mat(:,14),mat(:,15)];
mat=input6;
in6=[mat(:,1),mat(:,2),mat(:,3),mat(:,4),mat(:,5),mat(: ,6),mat(:,7),mat(:,8),mat(:,9),mat(:,10),mat(:,11) ,mat(:,12),mat(:,13),mat(:,14),mat(:,15)];
mat=input7;
in7=[mat(:,1),mat(:,2),mat(:,3),mat(:,4),mat(:,5),mat(: ,6),mat(:,7),mat(:,8),mat(:,9),mat(:,10),mat(:,11) ,mat(:,12),mat(:,13),mat(:,14),mat(:,15)];
mat=input8;
in8=[mat(:,1),mat(:,2),mat(:,3),mat(:,4),mat(:,5),mat(: ,6),mat(:,7),mat(:,8),mat(:,9),mat(:,10),mat(:,11) ,mat(:,12),mat(:,13),mat(:,14),mat(:,15)];
inMatGlobal=[in1;in2;in3;in4;in5;in6;in7;in8];


%normalize input
%inputNormal=normalizeInput(inMatGlobal);

for i=1:15
col=inMatGlobal(:,i);
mean1=mean(col);
var1=var(col);
for j=1:264
col(j)=(col(j)-mean1)/var1;

end;
out2(:,i)=col;

end;
inputNormal=out2;

%method 2 with sqrt
for i=1:15
col=inMatGlobal(:,i);
mean1=mean(col);
var1=sqrt(var(col));
for j=1:264
col(j)=(col(j)-mean1)/var1;

end;
out3(:,i)=col;

end;
inputNormalSqrt=out3;

%method 2 with max
for i=1:15
col=inMatGlobal(:,i);
mean1=mean(col);
mx=max(col)+.1;
for j=1:264
col(j)=(col(j)-mean1)/mx;

end;
out4(:,i)=col;

end;
inputNormalMax=out4;

%making output of nn
outMat=-1*ones(33,33);
for i=1:33
outMat(i,i)=1;
end;

outNormal=[outMat;outMat;outMat;outMat;outMat;outMat;outMat;o utMat];
%csvwrite('c:\inputNormal.dat',inputNorm al);
%csvwrite('c:\outputNormal.dat',outNorma l);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

net = mlp(15, 33, 33, 'linear'

% Set up vector of options for the optimiser.
options = zeros(1,18);
options(1) = 1; % This provides display of error values.
options(9) = 1; % Check the gradient calculations.
options(14) = 1000; % Number of training cycles.

% Train using scaled conjugate gradients.
[net, options] = netopt(net, options, inputNormal, outNormal, 'scg'

% Plot the trained network predictions.
test=inputNormal(33,;
y = mlpfwd(net, test);
y'




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