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.

Sample Structure

Backpropagation Neural Network
Backpropagation Neural Network

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
Neural Net Components in an Object Oriented Class Structure