Update the Winning Node

The next step is to adjust the vector at the winning node so that its weights become more like those of the sample pattern. 

If the learning rate was 0.05, the node weights after updating would be 

As the adjustments at the winning node move each of its weights slightly toward the corresponding element of the sample vector, the node learns a little about this sample pattern and, thus, is more likely to again be the 

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