How to define error weights in Neural Network?

I want to minimize a mean squared weighted deviation in a neural network. The weights are different for each sample.

How can I specify this?

Is it perform(net,t,y,ew)?

ew = [a b c d ...] (weight for each sample)

Answer 1

[Greg Heath]

The documentation commands 

help train
doc train

yield

[NET,TR] = train(NET,X,T,Xi,Ai,EW)

Hope this helps.

Greg

Answer 2

[Greg Heath]

Yes.

However, I would scale the data so that the maximum weight is unity.

Hope this helps.

Thank you for formally accepting my answer

Greg

[Anderson]

Hi Greg,

When I do perform(net,t,y,ew), the training process does not consider the weights. How can I include the weights in the training?

If I scale the weights (wide range interval), it will not loose information?