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Convert neural network closed-loop feedback to open loop


net = openloop(net)
[net,xi,ai] = openloop(net,xi,ai)


net = openloop(net) takes a neural network and opens any closed-loop feedback. For each feedback output i whose property net.outputs{i}.feedbackMode is 'closed', it replaces its associated feedback layer weights with a new input and input weight connections. The net.outputs{i}.feedbackMode property is set to 'open', and the net.outputs{i}.feedbackInput property is set to the index of the new input. Finally, the value of net.outputs{i}.feedbackDelays is subtracted from the delays of the feedback input weights (i.e., to the delays values of the replaced layer weights).

[net,xi,ai] = openloop(net,xi,ai) converts a closed-loop network and its current input delay states xi and layer delay states ai to open-loop form.


Convert NARX Network to Open-Loop Form

This example shows how to create a NARX network in open-loop form, convert it to closed-loop form, and then convert it back.

[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);


Yopen = net(Xs,Xi,Ai);
net = closeloop(net);

[Xs,Xi,Ai,Ts] = preparets(net,X,{},T);
Yclosed = net(Xs,Xi,Ai);
net = openloop(net);

[Xs,Xi,Ai,Ts] = preparets(net,X,{},T);
Yopen = 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