The Multi-Layer-Perceptron was first introduced by M. Minsky and S. Papert in 1969.
It is an extended Perceptron and has one ore more hidden neuron layers between its input and output layers.
Due to its extended structure, a Multi-Layer-Perceptron is able to solve every logical operation, including the XOR problem.
|Neuron layers||1 input layer, 1 or more hidden layer(s), 1 output layer|
|Input value types||binary|
|Activation function||hard limiter / sigmoid|
|Learning algorithm||delta learning rule, backpropagation (mostly used)|
|Mainly used in||complex logical operations, pattern classification|