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November 28th, 2012, 12:37 PM  #1 
Newbie Joined: Nov 2012 Posts: 1 Thanks: 0  Neural networks  backpropagation
Hi, I am trying to learn neural networks and I am reading a book called: Machine Learning: An Algorithmic Perspective. This book can be found from google books. Hopefully this link works: (http://books.google.com/books?id=n66O8a4SWGEC&hl=fi) I am not able to follow what happens in formula 3.48 on page 90. I can not understand why the h_k is equivalent with only one activation function instead of sum of activation functions multiplied with weights. Can somebody explain origin of formula 3.48 in more details? Thanks 

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backpropagation, networks, neural 
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