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!
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