Neural Network in matlab: How to specify input weights - neural-network

Question

I need help rectifying this code to implement XOR using Neural Network in matlab. But, I am unable to set the input weights from the input layer to the first layer. The network has input layer, hidden layer and output layer of 2,2 and 1 neurons respectively.
Can somebody help me with this?
net=network;
net.numInputs = 1;
net.inputs{1}.size = 2;
net.numLayers = 2;
net.layers{1}.size = 2;
net.layers{2}.size = 1;
net.inputConnect(1) = 1;
net.layerConnect(2, 1) = 1;
net.outputConnect(2) = 1;
net.targetConnect(2) = 1;
net.layers{1}.transferFcn = 'logsig';%>> net.layers{2}.transferFcn = 'purelin';
net.layers{2}.transferFcn = 'logsig';
net.biasConnect = [ 1 ; 1];
net.layers{1}.initFcn = 'initwb';
net.layers{2}.initFcn = 'initwb';
net.inputWeights={1 1;1 1};%ask this. error is not explanatory. probably syntax.
net.biases{1}={-1.5 -0.5};
net.biases{2}=-0.5;
net.layerWeights{2,1}={-2 1};
P=[0 1 0 1;0 0 1 1];
T=[0 1 1 0];
net.initFcn = 'initlay';
net = init(net);
net.adaptFcn = 'adaptwb';
net.inputWeights{1,1}.learnFcn = 'learnp';
net.biases{1}.learnFcn = 'learnp';
net.adaptParam.passes =3;
net.performFcn = 'mse';
y = sim(net,P)

Answer 1

doc network tells me:
If net.inputConnect(i,j) is 1, then net.inputWeights{i,j} is a structure
defining the weight to layer i from input j.
So instead of setting a cell array for the net.inputWeights you should be setting the elements of net.inputWeights for each combination of input and first-layer nodes like this:
net.inputWeights{1,1} = weight11; % input1 node 1
net.inputWeigtts{1,2} = weight12; % input1 node 2
...