Architecture of the proposed neural comparator, with intermediate layers x⁽²⁾ and x⁽³⁾ and output x⁽⁴⁾. The comparator autonomously learns to compare the inputs y and z. The output is close to zero when the two inputs are identical or correlated and close to unity when they are different or uncorrelated.