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Weight Updates Calculated

Weight Updates Calculated

Understand the weight update method in a neural network with the help of a numerical example.

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An example of calculating a weight update

The following network is one we’ve worked with before, but this time we’ve added example output values from the first hidden node oj=1o_{j=1} and the second hidden node oj=2o_{j=2}. These are just made-up numbers to illustrate the method and aren’t properly worked out by feeding signals forward from the input layer.

Update weights to reduce error in neural network
Update weights to reduce error in neural network

We want to update the weight w11w_{11} between the hidden and output layers, which currently has the value 2.02.0.

Let’s write out the error slope again:

Ewjk=(tkok)sigmoid(jwjkoj)(1sigmoid(jwjkoj))oj\frac{\partial E}{\partial w_{jk}} = -(t_k - o_k)\cdot \text{sigmoid}\left(\sum_j w_{jk} \cdot o_j \right) \left(1-\text{sigmoid}\left(\sum_j w_{jk} \cdot o_j\right)\right)\cdot o_j ...