berke@CS.UCLA.EDU (11/02/87)
Many connectionist researchers have asserted that a distributed representation provides efficient use of resources, encoding 2**n patterns in n units. The "2**n states for n units" argument is sketched below: Replace unit-encoding (grandmother cells) with patterns of activation over n (binary) units. Instead of representing only n distinct "events," one with each unit, we can represent up to 2**n events using only n units. These patterns overlap, and this overlap can be used to gain "associative" recall. Does anyone have any references to such arguments? I've heard this argument made verbally, but I don't recall exact references in print. Do you? Also, is there a net-convention for 2 to-the-n? I'm using 2**n above, (a vestige of my early FORTRAN experience?) which I prefer to 2^n. Anyone have any others? Perhaps it would be appropriate to "r" a reply to me rather than posting a follow-up to net. If they are many or interesting, I'll be sure to post them in one batch. I would appreciate exact quotes, with references including page numbers so that I could find the, as the NLP people say, context. Thanks Pete