MATLAB: How to create a 2 x 0 empty cell array variable

empty cell notation

% As a result of help and doc narxnet neural network documentation, I get the following result

 [ X, T ]            =  simplenarx_dataset;
 neto                =  narxnet( 1:2, 1:2, 10 );
 [ Xo, Xoi, Aoi, To] =  preparets( neto, X, {}, T );
 whos
 %   Name   Size   Bytes  Class  
 %   Aoi    2x0      0     cell

% Now I am curious: What straight forward line command will create a 2 x 0 cell?

% To get a hint, I entered the two commands

>> Aoi , Aoi = Aoi

Aoi = 2×0 empty cell array

% Again: What straight forward line command will create a 2 x 0 cell ?

 E = { ? }, whos E

Thanks,

Greg

Best Answer

cell(2,0)

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MATLAB: How to train NARX neural network in closed loop

 close all, clear all, clc
disp('DIRECT TRAINING OF A CLOSELOOP NARXNET')
load('maglev_dataset');
whos
%   Name              Size      Bytes   Class 
%   maglevInputs      1x4001    272068  cell                
%   maglevTargets     1x4001    272068  cell                
X   = maglevInputs; 
T   = maglevTargets;
ID  = 1:2, FD = 1:2, H  = 10   % Default values
netc                    = closeloop(narxnet(ID,FD,H));
view(netc)
netc.divideFcn          = 'divideblock';
[ Xcs, Xci, Aci, Tcs ]  = preparets( netc, X, {}, T );
tcs                     = cell2mat(Tcs);
whos X T Xcs Xci Aci Tcs tcs
%  Name     Size     Bytes   Class
%   Aci     2x2         416  cell                
%   T       1x4001   272068  cell                
%   Tcs     1x3999   271932  cell                
%   X       1x4001   272068  cell                
%   Xci     1x2         136  cell                
%   Xcs     1x3999   271932  cell                
%   tcs     1x3999    31992  double              
 MSE00cs = var(tcs,1)  % 2.0021 ( 1-dim MSE reference)
 rng(4151941)
tic
[netc trc Ycs Ecs Xcf Acf ] = train(netc,Xcs,Tcs,Xci,Aci);
toc                           % 197 sec
view(netc)
whos Ycs Ecs Xcf Acf
%   Name    Size     Bytes     Class
%   Acf     2x2         416    cell               
%   Ecs     1x3999   271932    cell               
%   Xcf     1x2         136    cell               
%   Ycs     1x3999   271932    cell               
 stopcriterion  = trc.stop                    % Validation stop
bestepoch      = trc.best_epoch               % 4
ecs            = cell2mat(Ecs);
NMSEcs         = mse(ecs)/MSE00cs             %  1.2843
tcstrn         = tcs(trc.trainInd);
tcsval         = tcs(trc.valInd);
tcstst         = tcs(trc.testInd);
NMSEcstrn      = trc.best_perf/var(tcstrn,1)  %  1.3495
NMSEcsval      = trc.best_vperf/var(tcsval,1) %  0.9325
NMSEcstst      = trc.best_tperf/var(tcstst,1) %  1.6109

I consider a good design to have a normalized MSE, NMSE <= 0.01 implying that 99% of the target variance is successfully modeled. Obviously this design is a failure.

However, as I mentioned before, my objective was to obtain an error free code for you.

Presumably, a search for the proper combination of ID, FD, H and RNG seed would yield a more successful design.

I will let you have fun with that.

I prefer to convert an openloop design as demonstrated in my reference.

MATLAB: As used in closed loop network NarX reality

I think the network is evaluated openloop and I think it gives good results,

What are I, N, ID, FD, H, Ntrn, Nval, Ntst, R2trn, R2trna, R2val and R2tst ?

but for now I do not believe them.

Why?
What do you get from the same data using closeloop?

My questions are as follows:

1 - I have evaluated the accuracy openloop, how would an in closeloop?. For a first simulation closeloop as inputs I have therefore created a matrix with the last two values InputSeries and say 30 inputs outside the training sample which would have an array of 2 * 32. To create the matrix newsTargets introduce targetSeries the last value of the array and fill with 31 NaN thereby get another matrix 1 * 32.

I don't understand where this data is coming from.

From here I simulate the network and gives me values that putting them together with real targets is a bit displaced. (I would like to send a screenshot of that graph, if you tell me in what way will send it). I think I perform the operation correctly, although I would like to evaluate the accuracy closeloop very strictly.

There is a way to see plots on ANSWERS. Fnd out how. Right now I need to see your code.

2 - My second question is because if I try the net for real, that is, suppose we are to March 4, 2013. I by a platform get data (RSI inputs and EMA), whereby I newInputs other matrix in which the last 2 introduce inputSeries values and RSI values and EMA today. (I think I'm doing well so far). To create another array newTarget do with the last value NaN targetSeries and 2 to have the same dimension as newInput (2 * 3) and newTarget (1 * 3) and performed the simulation to obtain the predicted value of the day March 5, 2013 . To continue iterating introduce the value of March 5 and get the value of the March 6, much like the network does NAR?, Is, in preparets command:

[inputs, inputStates, layerStates, targets] = preparets (net, inputSeries, targetSeries);?? and evaluate the network outside the sample.

Basically these are my doubts.

 I don't understand. Post the code.

Greg

Best Answer

Related Solutions

MATLAB: How to train NARX neural network in closed loop

MATLAB: As used in closed loop network NarX reality

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