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