openloop

(To be removed) Convert neural network closed-loop feedback to open loop

openloop will be removed in a future release. For more information, see Transition Legacy Neural Network Code to dlnetwork Workflows.

For advice on updating your code, see Version History.

Syntax

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


Description

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.

Examples

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);

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);
net = openloop(net);
view(net)

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

Version History

Introduced in R2010b

R2026a: openloop will be removed

openloop will be removed in a future release.

To train a neural network with time series data, use one of these options:

• Time Series Modeler app — Interactively design and train neural networks for time series data.

• trainnet — Train neural network. Use this function when you need more flexibility in the network architecture or training algorithm.

To learn more about time series data workflows, see these examples and topics:

• Training Neural Networks with Time Series Data

• Time Series Forecasting Using Deep Learning

• Create and Train NARX Network for Time Series Forecasting

• Long Short-Term Memory Neural Networks

• Example Deep Learning Network Architectures

For more information, see Transition Legacy Neural Network Code to dlnetwork Workflows.