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);
