title: about backpropagation and sigmoid function
body: <p>I have been reading this ebook about ANN:<a href="https://www4.rgu.ac.uk/files/chapter3%20-%20bp.pdf" rel="nofollow">https://www4.rgu.ac.uk/files/chapter3%20-%20bp.pdf</a></p>
  
  <p>and got a doubt about the effect of the sigmoid function for calculating the errorB. In the text says that if I have threshold neuron I can use:</p>
  
  <p>Target-Output</p>
  
  <p>but because I have a sigmoid function involved I should add:</p>
  
  <p>Output(1-Output)</p>
  
  <p>and end up with:</p>
  
  <p>ErrorB=OutputB(1-OutputB)(TargetB-OutputB)</p>
  
  <p>I mean why I should add the part of O(1-O), I have tried with different values, but I really do not get the intuition why it should be in that way.</p>
  
  <p>Any help?</p>
  
  <p>Thanks</p>