Code covered by the BSD License

# Neural Network Classifiers

05 Nov 2007 (Updated 09 Nov 2011)

Mex implementation of 3 majors neural networks classifiers.

normalize.m
```function x = normalize(x , methode)

%
% x = normalize(x , [methode=1]);
%
%
%
% Author : Sbastien PARIS : sebastien.paris@lsis.org
% -------

if (nargin < 2)

methode                           = 1;

end

if(methode == 0)

return;

end

if (methode == 1)

mindata                           = min(x , [] , 2);

maxdata                           = max(x , [] , 2);

temp                              = maxdata - mindata;

temp(temp==0)                     = 1;

x                                 = 2*(x - mindata(: , ones(1 , size(x , 2))))./(temp(: , ones(1 , size(x , 2)))) - 1;

end

if (methode == 2)

mx                            = mean(x , 2);

res                           = x - mx(: , ones(1 , size(x , 2))) ;

stdx                          = sqrt(1/(size(x , 2) - 1)*sum(res.*res , 2));

stdx(stdx==0)                 = 1;

x                             = res./stdx(: , ones(1 , size(x , 2)));

end

if (methode == 3)

mindata                       = min(x(:));

x                             = log(x - mindata + 1 +eps);

mx                            = mean(x , 2);

res                           = x - mx(: , ones(1 , size(x , 2))) ;

stdx                          = sqrt(1/(size(x , 2) - 1)*sum(res.*res , 2));

stdx(stdx==0)                 = 1;

x                             = res./stdx(: , ones(1 , size(x , 2)));

end

if (methode == 4)

mindata                       = min(x(:));

x                             = 1./(1 + exp(-(x - mindata)));

%     mx                            = mean(x , 2);
%
%     res                           = x - mx(: , ones(1 , size(x , 2))) ;
%
%     stdx                          = sqrt(1/(size(x , 2) - 1)*sum(res.*res , 2));
%
%     x                             = res./stdx(: , ones(1 , size(x , 2)));

end```