void NNetwork::propigateActivations(){

/*
 This is the math I am using
[W1 W2   [I1, I2, B1]
 W3 W4
 W5 W6]

 H1 = I1*W1 + I2*W3 + B1*W5
 H2 = I1*W2 + I2*W4 + B1*W6
*/

// Calculate the activations for the hidden layer
for (int i = 0; i < hidUnits - 1; i++) {

    for (int j = 0; j < inUnits; j++) {
        nNetwork->hiddenLayer.x[i] += nNetwork->inputLayer.w[j][i] * nNetwork->inputLayer.x[j];
    }
}

// Use the the Sigmoid function: on the hidden layer
for(int i = 0; i < hidUnits - 1; i++){
    // fast sigmoid algorithm is f(x) = x / (1 + abs(x))
    nNetwork->hiddenLayer.x[i] = nNetwork->hiddenLayer.x[i] / (1 + abs(nNetwork->hiddenLayer.x[i]));
}


// Set bias node for hidden layer to 1.0
nNetwork->hiddenLayer.x[hidUnits - 1] = 1.0;

// Calculate the activations for the output layer
for (int i = 0; i < outUnits; i++) {

    for (int j = 0; j < hidUnits; j++) {
        nNetwork->outputLayer.x[i] += nNetwork->hiddenLayer.w[j][i] * nNetwork->hiddenLayer.x[j];
    }
}

// Use the the Sigmoid function: on the output layer
for(int i = 0; i < outUnits; i++){
    // fast sigmoid algorithm is f(x) = x / (1 + abs(x))
    nNetwork->outputLayer.x[i] = nNetwork->outputLayer.x[i] / (1 + abs(nNetwork->outputLayer.x[i]));
}