Cascade-forward neural network
Cascade-forward networks are similar to feed-forward networks, but include a connection from the input and every previous layer to following layers.
As with feed-forward networks, a two-or more layer cascade-network can learn any finite input-output relationship arbitrarily well given enough hidden neurons.
Row vector of one or more hidden layer sizes (default = 10)
Training function (default =
and returns a new cascade-forward neural network.
Here a cascade network is created and trained on a simple fitting problem.
[x,t] = simplefit_dataset; net = cascadeforwardnet(10); net = train(net,x,t); view(net) y = net(x); perf = perform(net,y,t)
perf = 1.9372e-05