How to predict future values by using Elman recurrent neural network (ERNN) in MATLAB R2012a?

I want to predict future values by 1 step ahead using ERNN. I have a dataset (which I name as 'ba') of size 1x120. But, when I follow the example, it gives me errors. I write as follows:

>> input=ba(1:119); >> target=ba(2:120); >> net=elmannet(1,10); >> [Xs,Xi,Ai,Ts]=preparets (net,input,target); >> net=train(net,Xs,Ts,Xi,Ai);

    Error using traingdx (line 108)
    Inputs and layer states have different
    numbers of samples.

    Error in network/train (line 106)
    [net,tr] =
    feval(net.trainFcn,net,X,T,Xi,Ai,EW,net.trainParam);

And, I also not sure what the 'layerdelays' in "elmannet(layerdelays,hiddenSizes,trainFcn)" means. I just put 1 because I think that I want to predict future values of 1 step ahead.

[Greg Heath]

Does it work on the simpleseries example in the documentation ?

 [X,T] = simpleseries_dataset;
 whos
%   Name      Size           Bytes  Class     
%   T         1x100            12000  cell               
%   X         1x100            12000  cell               

 input =T(1:99); 
 target=T(2:100); 
 net=elmannet(1,10);
 [Xs,Xi,Ai,Ts]=preparets (net,input,target); 
 net=train(net,Xs,Ts,Xi,Ai);

[Greg Heath]

I forgot to mention that the documentation states that ELMANNET is obsolete and recommends NARXNET instead.

Answer 1

[Greg Heath]

help elmannet
doc elmannet

[soo rachael]

I have followed the example (program written as above), but I still got the errors. What was going wrong?