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.
|Neuron layers||1 input layer, 1 or more hidden layer(s), 1 output layer|
|Input value types||binary|
|Mainly used in||complex logical operations, pattern classification, speech analysis|