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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:

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And how to provide weight and bias coefficients of this network?

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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.

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