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developerWorks: Weave a Neural Net with Python

Jun 21, 2004, 07:00 (0 Talkback[s])
(Other stories by Andrew L. Blais)

"Hot things cool, obviously. The house gets messy, frustratingly. In much the same way, messages are distorted. Short-term strategies for reversing these things include, respectively, reheating, cleaning, and the Hopfield net. This article introduces you to the last of these three, an algorithm that can, within certain parameters, undo noise. A very simple Python implementation, net.py, will show you how its basic parts fit together, and why a Hopfield net can sometimes retrieve a pattern from its distortion. This implementation, while limited, will still enable you to perform a number of instructive and revealing experiments on the Hopfield net.

"I assume that you are reading this because you have some computational problem. You have been advised that some neural net algorithm might provide a solution. Specifically, the suggestion is that you might employ a Hopfield net. I suppose further that you need a precis of the idea so you can decide whether the suggestion is feasible and warrants more exploration. The following broadly sketched application of the Hopfield net may get you started solving your problem..."

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