Perceptron Limitations
Perceptron training always converges if the training data X+ and X- are linearly separable sets.
The boolean function XOR (exclusive or) is not linearly separable. (Its positive and negative instances cannot be separated by a line or hyperplane.) It cannot be computed by a single-layer perceptron. It cannot be learned by a single-layer perceptron.