A Theory of Sleep
yan king yin (no spam please)
y.k.y at lycos.com
Wed Aug 15 01:00:41 EST 2001
When I said "random" it also means under genetic and other constrains. I
know whether to call it "chaotic" or "quasi-random".
Generating excess combinations and then eliminating them is quite common
in biological systems, such as in the immune sytem and in the nervous
"Ed van der Meulen":
> Sleep functions are in my view important for all kinds of
> neural nets, mainly dealing with it's inner unrest.
> On the site http://nnw.sourceforge.net you can find
> demos of neural nets having a few sleep functions. And if
> you know how important categorizing is for our human
> intelligence, you can't underestimate these sleep function.
> But randomize synaptic connections is for me too wild.
> All happens with all kinds of constraints. In my models
> I certainly do use variation with some amount of chaos,
> which is inherent in the signals and some in the neurons.
> Internal generated signals have indeed some chaos, but
> the overall behavior is fairly logical.
> Important also is the large difference in the size scales,
> between a single connection and overall behavior,
> which I see as emerging with often unpredictable
> behavior, however frequently within bounds.
> I tell you the clue of my view. It's very simple in my project,
> look at a level of detail (LOD) or scale where you don't see
> the individual neurons anymore, but only streams. Those
> streams can stream forward and sometimes backward.,
> with only a few extra features. The number of degrees of
> freedom is low on this LOD. We have coded those
> streams, that simple. But we've lost the knowledge that our
> cell is the representant of one real neuron, it could stand
> for a cluster of cells, but with the amazing bottom-up
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