A multi-layer perceptron is an early multi-layer neural network architecture that had precisely three layers: input, hidden and output. The combination of sigmoid threshold functions and backpropagation enabled the inner hidden layer to learn weights, thus beginning the modern field of neural networks.
Used in glossary entries: backpropagation, multi-layer neural network, neural network, sigmoid function
A multi-layer perceptron architecture.
A simple multi-layer perceptron to solve the XOR problem.