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I've been using this tutorial for my reference on coding backpropagation. But, today, I've found another tutorial that has used same reference with me but with another approach in changing of synapse weight. What's different about the both of approach?

EDIT

Thank you Renan for your quick response.

The main difference is:

  1. First method is changing the synapse weight after calculate delta in each neuron (node).
  2. On the second method, The delta is calculated after calculate synapse weight based on delta from layer above.

note: I'll edit this explanation if still not clear. Thanks.

Community
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Pattisahusiwa
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  • Instead of linking to both sites and expect us to read the whole of those tutorials, you should describe both methods here. – Geeky Guy Sep 05 '13 at 20:53

1 Answers1

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Equal calculations

Since the delta for the current layer depends of the weight layer between the layer above and the current layer, both of the methods is correct.

But it would not be correct to adjust the input weights to a layer before calculating the delta for the layer below!

The equation

enter image description here

Here you can see the mathmatical equation for calculating the derivative 
of the Error with respect to the weights depends on the weights between 
this layer and the layer above. (using Sigmoid)
O_i = the layer below   # ex: input
O_k = the current layer # ex: hidden layer
O_o = the layer above   # ex: output layer
jorgenkg
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