Backpropagation Net

The Backpropagation Net was first introduced by G.E. Hinton, E. Rumelhart and R.J. Williams in 1986 and is one of the most powerful neural net types. It has the same structure as the Multi-Layer-Perceptron and uses the backpropagation learning algorithm.

Type	feedforward
Neuron layers	1 input layer, 1 or more hidden layer(s), 1 output layer
Input value types	binary
Activation function	sigmoid
Learning method	supervised
Learning algorithm	backpropagation
Mainly used in	complex logical operations, pattern classification, speech analysis

Sub-sections