Question
inputDelays = 1:delay; hiddenLayerSize = 1; net = narxnet(inputDelays,feedbackDelays,hiddenLayerSize); [inputs,inputStates,layerStates,targets] = preparets(net,inputSeries,{},targetSeries); net.divideParam.trainRatio = 70/100; net.divideParam.valRatio = 30/100; [net,tr] = train(net,inputs,targets,inputStates,layerStates); nets = removedelay(net); a = nets.IW{1,1}; b = nets.IW{1,2}; c = nets.b{1}; d = nets.lw{2,1}; e = nets.b{2}; tansig(a * 1 + b * 11 + c) *d + e inputSeries = tonndata(1,true,false); targetSeries = tonndata(11,true,false); [xs,xis,ais,ts] = preparets(nets,inputSeries,{},targetSeries); ys = cell2mat( nets(xs,xis,ais)) Dear all, I am trying to replicate what the NARX network does. I am using the above code, and I am not getting correct results. In particular, ys is what you'd expect (12), but my replication using matrix multiplication is an order of magnitude wrong. What am I doing wrong? Thank you very much!
Expert Answer
Kshitij Singh
PhD Expert
Answered Aug 20, 2026
1. Please refrain from using numbers (e.g., 1, 11 and 12)
as variables
2. Show some results using the MATLAB narxnet data
obtained from the commands
a. help narxnet and/or doc narxnet
b. help nndatasets and/or doc nndatasets
3. Post enough information so that your work can be
duplicated, e.g.,
a. values of both delays
b. initial state of the random number generator
4. See some of my examples in the NEWSGROUP and ANSWERS by searching with
narxnet tutorial and narxnet
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