Same algorithm runs much slower in vb .net 3.5 than in matlab

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Hi guys,

I am trying to implement a neural network training algorithm in vb .net. I have found a open-source matlab code of this algorithm, so basically I am simply converting the matlab code to vb and adding some UIs.

Right now I have already finished the job (they are getting the same results if the same data was tested), but the program runs much much slower in vb than in matlab, like about 30 times! What I did is just to run a small function and to compare the running time.

Here are the codes of the function (VB .NET):

Public Function CalculateError(ByVal input As Matrix, ByVal output As Matrix) As Double
        Dim result As Double
        result = 0
        Dim Nm, Nn, Ni, No As Integer
        Dim net As Double
        Nm = input.mRow
        Nn = CInt(parameters.value(2))
        Ni = CInt(parameters.value(4))
        No = CInt(parameters.value(5))

        For p As Integer = 1 To Nm
            Dim temp = New List(Of Double)
            'compute the first Ni entries of temp
            For i As Integer = 1 To Ni
                temp.Add(input.value(p, i))
            Next

            For n As Integer = 1 To Nn
                net = weights.value(iw.value(n))
                For i As Integer = iw.value(n) + 1 To iw.value(n + 1) - 1
                    'Make sure topology is a matrix with integer entries only
                    net += temp(topology.value(i) - 1) * weights.value(i)
                Next

                temp.Add(ActivationFunction(n, net))
                'temp.Add(0.0)
            Next



            For k As Integer = 1 To No
                result += Math.Pow(output.value(p, 1) - temp(Nn + Ni - No + 1 - 1), 2)
            Next

        Next


        ' SSE
        Return result
    End Function

and matlab:

function [err] = calculate_error(input,output, topo, weight,param, iw, gain, act)
err = 0;
for p = 1:size(input, 1)     % number of patterns
   temp(1:param(4)) = input(p,1:param(4));
   for n = 1:param(2) % number of neurons
      j = param(4) + n;
      net = weight(iw(n));
      for i = (iw(n)+1):(iw(n+1)-1)
         net = net + temp(topo(i))*weight(i);
      end;
      tic
      out=actFunc(n,net,act,gain);
      toc
      temp(j) = out;
   end;
   for k = 1:param(5)
      err = err + (output(p,k)-temp(param(2)+param(4)-param(5)+k))^2;                % calculate total error
   end;
end;

The Matrix is a custom class I defined and it is implemented using Array; ActivationFunction is another simple function (I will attach the code also); and other variables like iw, weights are some internal variables, I don't think they really affect the runnning time much.

The code for ActivationFunction is:

Public Function ActivationFunction(ByVal n As Integer, ByVal net As Double) As Double
        'Dim result As Double
        Select Case activations.value(n)
            Case 0
                Return gain.value(n) * net           'linear neuron
            Case 1
                Return 1.0 / (1.0 + System.Math.Exp(-1.0 * gain.value(n) * net))     'unipolar neuron
            Case 2
                Return 2.0 / (1.0 + System.Math.Exp(-1.0 * gain.value(n) * net)) - 1.0     'bipolar neuron
            Case 3
                Return (gain.value(n) * net) / (1.0 + gain.value(n) * System.Math.Abs(net))     'unipolar elliot neuron
            Case 4
                Return (2.0 * gain.value(n) * net) / (1.0 + gain.value(n) * System.Math.Abs(net)) - 1     'bipolar elliot neuron
        End Select
    End Function

The problem I have now is that I tried to run these two CalculateError functions (one in vb. net and other in matlab), the vb code needs like 50 milliseconds, while the matlab code runs in 1.5 millisecond! BTW, even for the ActivationFunction (even simpler), matlab runs much faster.

Anyone can help me with this or any idea that why the VB code is that slow?

TIA.