closeloop
Convert neural network open-loop feedback to closed loop
Syntax
net = closeloop(net)
[net,xi,ai] = closeloop(net,xi,ai)
Description
net = closeloop(net) takes a neural network and closes any open-loop
feedback. For each feedback output i whose property
net.outputs{i}.feedbackMode is 'open', it replaces its
associated feedback input and their input weights with layer weight connections coming from the
output. The net.outputs{i}.feedbackMode property is set to
'closed', and the net.outputs{i}.feedbackInput property
is set to an empty matrix. Finally, the value of
net.outputs{i}.feedbackDelays is added to the delays of the feedback layer
weights (i.e., to the delays values of the replaced input weights).
[net,xi,ai] = closeloop(net,xi,ai) converts an open-loop network and
its current input delay states xi and layer delay states
ai to closed-loop form.
Examples
Convert NARX Network to Closed-Loop Form
This example shows how to design a NARX network in open-loop form, then convert it to closed-loop form.
[X,T] = simplenarx_dataset;
net = narxnet(1:2,1:2,10);
[Xs,Xi,Ai,Ts] = preparets(net,X,{},T);
net = train(net,Xs,Ts,Xi,Ai);
view(net)
Yopen = net(Xs,Xi,Ai); net = closeloop(net); view(net)
[Xs,Xi,Ai,Ts] = preparets(net,X,{},T);
Yclosed = net(Xs,Xi,Ai);Convert Delay States
For examples on using closeloop and openloop to
implement multistep prediction, see narxnet and narnet.
Version History
Introduced in R2010b
