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BCM / Hebbian Learning in ANNs

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I'm typically somewhat resourceful regarding search engines, but I'm having some difficulty regarding BCM/Hebbian learning tutorials. I'm very interested in putting together a demo for myself using both types of learning. There is no purpose to either of them for myself other than that I'm interested, so any simple usages of either learning method would be great. I try to state in most of my threads that my understanding of mathematical notation is limited, very. Just to say, I do understand the concept behind both learning methods, just not the whole picture to a point of putting them into practice. From the little I do understand, Hebbian learning is the older and more unstable form in comparison to BCM? If that is accurate, BCM would of course be what I would prefer to learn. Oh, and if there isn't anyone that feels comfortable trying to help explain it to me, I'd be just as happy (maybe more so) for a reading material suggestion. Thanks, Mythics

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This tutorial seems accessible: http://www.csse.monash.edu.au/courseware/cse2330/2006/04/Pracs/prac3.pdf

It also has some code (for Matlab), which will probably help you understand.

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Looks like a rather well written tutorial. Thanks for the link. If I have any luck implementing it, I'll be sure to let you know.

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