How do we design a neural network with one hidden layer, two hidden neurons and an output neuron that implements an XNOR function? The truth table of XNOR is given below:
And how to provide weight and bias coefficients of this network?
$\begingroup$
$\endgroup$
Add a comment
|
$\begingroup$
$\endgroup$
Combine a NN for x1 AND x2 [your a1] with a NN for (NOT x1) AND (NOT x2) [your a2] to get the XNOR. You end up with inputs +1, x1, and x2 going to your hidden neurons a1 and a2, then +1, a1, and a2 into your output neuron.
