Documentation

This is machine translation

Translated by Microsoft
Mouse over text to see original. Click the button below to return to the English verison of the page.

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);
Ycloesed = net(Xs,Xi,Ai);

Convert Delay States

For examples on using closeloop and openloop to implement multistep prediction, see narxnet and narnet.

See Also

| | |

Introduced in R2010b

Was this topic helpful?