Abstract
Minsky and Papert (Perceptons: An Introduction to Computational Geometry, MIT Press: Cambridge, MA, 1969) show that a two-layer perceptron with monotonic activation function cannot solve the Xor problem. We present a two-layer perceptron with non-monotonic activation function which can separate non-linearly separated sets of data. This kind of perceptron is the applied to the Xor problem, parity problem and a pattern recognition problem. Learning strategy is detailed, and performance is evaluated.
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