14-10-2014, 07:43 PM
Description
Feedforward networks consist of a series of layers. The first layer has a connection from the network input. Each subsequent layer has a connection from the previous layer. The final layer produces the network's output.
Feedforward networks can be used for any kind of input to output mapping. A feedforward network with one hidden layer and enough neurons in the hidden layers, can fit any finite input-output mapping problem.
Specialized versions of the feedforward network include fitting (fitnet) and pattern recognition (patternnet) networks. A variation on the feedforward network is the cascade forward network (cascadeforwardnet) which has additional connections from the input to every layer, and from each layer to all following layers.