MATLAB: How to get predicted values from an open-loop Narxnet following other predicted values? Or is just possible with closed loop

closed loopnarxnetNetworkneuralopen loopprediction

I´m trying, once the net its trained, to get the net´s prediction of the trained data divided in 10 values predicted each time. I mean, it predicts the 10 first values, then the following 10 and so on. My question is if this is possible with an open-loop configuration of the net or its just possible with a closed-loop configuration, and if it is how.

Thank you beforehand

Best Answer

Using the openloop configuration requires a target input. When you run out of target data you have to use the closeloop configuration.

I have many posts in the NEWSGROUP and ANSWERS on both topics. Just add greg to the rest of your search words.

Hope this helps.

Thank you for formally accepting my answer

Greg

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In general, PREPARETS will yield the correct inputs. However, for TIMEDELAYNET, just use common sense:

 Ai = {}    % There is no feedback
 Xi = Xnew2(:,1:10);
 Xnew2s = Xnew2(:, 10:end);

Hope this helps.

Thank you for formally accepting my answer

Greg

PS: See my tutorials

MATLAB: NARXNET closed-loop vs open-loop

 % NARXNET closed-loop vs open-loop
 % Asked by Yevgeniy Arabadzhi 
 % 8:38 PM Thursday, November 3, 2016 
 %  
% I have three questions regarding the difference between 
% a closed-loop and an open-loop narxnet, and it's behavior.
% 
% First, a little about the problem I'm trying to solve. I 
% have an 2xN dimensional matrix of observation (X), from 
% which I'm trying to predict an output Y, 1xN. Now, a 
% narxnet takes as input both X and Y. The Matlab 
% documentation says that an open-loop narxnet finds a 
% function 'f' where y(t) = f( y(t-1), y(t-2), x(t-1), 
% x(t-2) ), for a delay of 2.

What you are overlooking is the role of the target; In fact, you never mention the target!

The target is used to design and operate the OL net. To emphasize this point I prefer to use the following notation:

 Uppercase for cells
 Lowercase for doubles and integers
 X,x for inputs
 T,t for targets
 Y,y for outputs
 i,j for timestep indices

% However, the results that I % get are much more accurate than I expect them to be. % This suggests that the narxnet uses the actual y(t) % as input as well.

ABSOLUTELY NOT! You just happened to have an easy problem (which you did not identify!). There are a variety of sample datasets in the help and doc documentations. Use the commands

 help nndatasets
 doc nndatsets

% When I convert the open-loop to a closed-loop, and retrain it, % I get much more reasonable results, not good, but reasonable.

Typically, when you convert from OL to CL and compare the results over the length of the target, you will get a spectrum of results: from excellent to lousy. Again, this will be demonstated if you try some of the sample datasets.

I have posted tutorials on narxnet design. I gather from this post that you are not familiar with them.

% 1.a) What is the actual input to an open-loop narxnet, % and the closed-loop. When trying to predict y(t), are the % inputs [ y(t), y(t-1), y(t-2), x(t-1), x(t-2) ] or % [ y(t-1), y(t-2), x(t-1), x(t-2) ], for both?

 ID = 1:2, FD = 1:2, H = 10    % DEFAULTs
 OL: y(i) =  f(x(i-1),x(i-2),t(i-1),t(i-2)); i = 3:N
 CL: y(i) =  f(x(i-1),x(i-2),y(i-1),y(i-2)); i = 3:N
 ID = 0:2, FD = 0:2, H = 10    
 OL: y(i) =  f(x(i),x(i-1),x(i-2),t(i),t(i-1),t(i-2)); i=3:N
 CL: y(i) =  f(x(i),x(i-1),x(i-2),y(i-1),y(i-2)); i = 3:N

NOTE THAT y(i) FEEDBACK IS NOT ALLOWED FOR CL !

% 1.b) For my problem I need the inputs to be [ y(t-1), % y(t-2), x(t), x(t-1), x(t-2) ], 0 to 2 delays on the X, % and 1 to 2 delays on the Y. How can I do that?

See above

% 2. For comparison, I've trained my open-loop, and tested % it, then convert the open-loop to a closed-loop using % netc = closeloop(net);

Next, compare the OL and CL on the OL design data.

% then trained the closed-loop from scratch and tested it. % I've read on MATLAB Answers that I should start training % the closed-loop with the weights from the open-loop net. % How can I used the weights of one net as the initial % weights for training another?

netc = closeloop(neto); netc = train(netc,X,Xoi,Aoi);

% 3. I understand that the narxnet uses a combination of % NNs and difference equations. I problem I run into when % using a closed-loop narxnet is that my predictions begin % to oscillate and explode exponential. I know that this % problem occurs in a difference equation, such as % y(t)=a*y(t-1)+b, when 'a' is greater than 1. What, in a % closed-loop narxnet could cause this similar issue?

Since the output containing errors is fed back to the input, the cause is, basically, similar.

% I didn't include any code because my questions need % high-level understanding and explanations, which I am % lacking. % % A huge thank you in advance, % % Yevgeniy

No, thank you. I'm sure more people than you realize will be thankful for this post.

Hope this helps

Greg

Best Answer

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