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I was learning self organizing feature maps the other day. I want to intuitively understand it because I'm not that good at math. But I still am not very clear about it. I can easily understand choosing a winner neuron and adjusting it's weights according to the sample. But what I cannot understand is the idea of the neighbourhood.

Why not update the winner, the neuron with the closest value to the sample, alone? What is the importance of updating close by neurons with it?

And why should you reduce the neighbourhood as you go on? Why not keep the neighbourhood just fixed at a value?

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  • $\begingroup$ The title you have chosen is not well suited to representing your question. Please take some time to improve it; we have collected some advice here. Thank you! $\endgroup$ – Raphael Apr 19 '16 at 13:17
  • $\begingroup$ In my experience, understanding mathematical concepts without mathematics is near impossible. You may want to start with the basics and work your way up. $\endgroup$ – Raphael Apr 19 '16 at 13:17

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