Is there a way to normalize data in bottom layer and pass it to the top layer?

[Wingwing Mok]

Hi all,

I am creating this topic to ask the question I describe in the subject. Basically, what I want to do is to normalize the data from bottom layer to the range [0,1] using the formula 

But I have no idea how to back propogate the gradient from the top layer based on this formula. Can anyone help me with some suggestions, either back-propogation about the formula or other way to do normalization?

Thanks!

i=xi−min(x)m

[anis....@shopedia.fr]

Hi
you can add a python layer to do the normalization :
please see this example of a python layer :http://stackoverflow.com/questions/34903975/how-to-create-caffedb-training-data-for-siamese-networks-out-of-image-directory