MATLAB: How to create the ownfitnet neural network? i have written code to calculate square root of number, plz help me to find the problem with it.

fitnet architecture

I have tried to create my own fitnet network to calculate square root of numbers, instead of using the matlab fitnet. the structure of my network is exactly like the fitnet architecture( I analyzed the fitnet architecture by looking at the script and object created of fitnet) but its not getting trained. plz check it and let me know what mistake I m making .
x=rand(1,1000)*150;
t=sqrt(x);
net=network();
net.adaptFcn='adaptwb';
net.numInputs=1;
net.inputs{1}.size=1;
net.numLayers=2;
net.layers{1}.size=10;
net.layers{2}.size=1;
net.inputConnect(1,1)=1;
net.layerConnect(2,1)=1;
net.biasConnect(1)=1;
net.biasConnect(2)=1;
net.biases{1}.learnFcn='learngdm';
net.biases{1}.initFcn='';
net.biases{2}.learnFcn='learngdm';
net.biases{2}.initFcn='';
net.outputConnect(2)=1;
net.layers{1}.transferFcn='tansig';
net.layers{2}.transferFcn = 'purelin';
net.inputweights{1,1}.initFcn='';
net.inputweights{1,1}.learnFcn='learngdm';
net.layerweights{2,1}.initFcn='';
net.layerweights{2,1}.learnFcn='learngdm';
net.inputs{1}.processFcns = {'removeconstantrows','mapminmax'};
net.outputs{2}.processFcns = {'removeconstantrows','mapminmax'};
net.divideFcn = 'dividerand'; % Divide data randomly
net.divideMode = 'sample'; % Divide up every sample
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;
net.trainFcn = 'trainlm';
net.performFcn = 'mse';
net.plotFcns = {'plotperform','plottrainstate','ploterrhist', … 'plotregression', 'plotfit'};
[net,tr] = train(net,x,t);
outputs = net(x);
test=100;
result = sim(net,test);

Best Answer

Replace
net.plotFcns = {'plotperform','plottrainstate','ploterrhist', ... 'plotregression', 'plotfit'};
with either
net.plotFcns = {'plotperform','plottrainstate','ploterrhist','plotregression', 'plotfit'};
or
net.plotFcns = {'plotperform','plottrainstate','ploterrhist',...
'plotregression', 'plotfit'};
HTH
Thank you for formally accepting my answer
PS: I recommend ALWAYS initializing the random number generator before the first creation of a random number. Then you can repeat your result.
Greg