Learning and generalization errors for the 2D binary perceptron

The statistical mechanics model of the binary perceptron learning is considered. It is proved that under the regularity conditions learning and generalization errors for the binary perceptron with two inputs tend to 0 at the average; the first term of the asymptotics is provided; its behavior with respect to the inverse temperature β does not coincide with that for the model with a smooth activation function.