A feedforward neural network is a directed acyclic graph, a network with two or more layers of nodes in which the signals travel unidirectionally, always from a layer to the next highest layer. If the network is fully connected, each node in a given layer has a weight connecting it to every node in the next layer. It is unusual and much more complicated to train a network if a node can be connected to a node that is not in the immediately succeeding layer.

Fully connected feedforward neural networks are useful for pattern classification and are often trained using the error backpropagation algorithm.