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))
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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