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# I was learning about Hebbian learning and figured, why not make an artifical neural network | |
# based on it? Actually, I should have been preparing a presentation on synaptic plasticity, and | |
# this seemed more interesting. At any rate, here it is. | |
# | |
# It doesn't work because of the limitations of Hebb's model, namely that | |
# at some point the network "discovers" something that sort of works, and from then on it feeds | |
# back on itself until the synaptic weights enter a positive feedback loop and cascade to | |
# infinity. | |
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