Neural Networks

[Leibnitz]

Does anyone knows how to implement a simple Neural Network using Backpropagation algorithm ?
any ideas or codes are welcome.

Thanks in advance !

 

[BoulderBum]

Believe it or not, I had to do this project for school. Unfortunately, I lost the backpropegation code, but I later developed an application ( in Java ) to handle Graham-Schmidt orthogonalization. It was one of my earlier works, so it's a little messy, but here's the logic: ( I'm sure you'll have no trouble converting it to C++ code, but give a shout if something in my code is unclear )

//orthogonalizes the vectors of a matrix

public double [][] GrahamSchmidt(double [][] ardat,
int row, int column)
{
double temp1,temp2;
double [] temp3;
temp3= new double[column];

double [][] V;
V= new double[row][column];

for (int n=0; n<row; n++) //loops all entries to N = row
{
temp1=0;
temp2=0; //resets temp
//variables to 0
for (int reset=0; reset<column;reset++)
temp3[reset]=0;

for(int p=n; p>=0; p--)
{
if (p==0)
//V=calculations
for (int Vset=0; Vset<column; Vset++)
{
V[n][Vset]=ardat[n][Vset]-temp3[Vset];
}

else
{
temp1 = 0;
temp2 = 0;

for (int loop1=0; loop1<column; loop1++)
{
//X*V(p-1)
temp1 += ardat[n][loop1]*V[p-1][loop1];
}

for (int loop2=0; loop2<column; loop2++)
{
//V(p-1)*V(p-1)
temp2 += V[p-1][loop2]*V[p-1][loop2];
}

if (temp2 == 0)
{
for (int loop3=0; loop3<column; loop3++)
{
temp3[loop3]+=0;
}
}
else
{
for (int loop3=0; loop3<column; loop3++)
{
//X* V(p-1)
//------------- * V(p-1)
//V(p-1)*V(p-1)

temp3[loop3]+=(temp1/temp2)*V[p-1][loop3];
} } // cuts else
} } //cuts current vector calculations
} //cuts all vectors to N loop
return V; //returns ortogonalized matrix
} //cuts method

hopefully it didn't get messed up with my editing and indentation correction.

Anyway, I have a question for you now; I forget what you must do for backpropegation after orthogonalizing a matrix. I remember something about multiplying the matrix by a weight vector or whatever, but I was hoping you could list all of the steps to fill me in.

Thanks in advance.

 

[Leibnitz]

Thanks for helping !
I'am myself a beginner with &quot;Neural Networks&quot;.
Here are some very useful links on &quot;Backpropation Neural Nets&quot;.
you probably will find what you are looking for in those links.

http://www.generation5.org/xornet.shtml

(in c++)

http://diwww.epfl.ch/mantra/tutorial/english/(

in Java)

http://www.cs.stir.ac.uk/~lss/NNIntro/InvSlides.html