In article <3740344e at news3.us.ibm.net>, Sergio Navega <snavega at ibm.net> wrote:
>Jiri Donat wrote in message <7hoift$1ie$1 at nnrp1.deja.com>...
>>>>To me, the biggest difference between natural NN and ANN is that every
>>digital simulation of ANN network has a discrete set of states (however
>>large the set is). This "limitation" (if we understand this feature of
>>digital representations of ANNs on today's computers as a limitation -
>>and some theories do) is inherited in our existing tools for ANN
>>simulations - in digital computers.
>>>>>I'm not sure I understand you here. In fact, biological neurons
>seen from "outside" are just things that fire or don't fire, in a
>purely discrete manner.
Seen from *FAR* outside, yes. In a similar fashion, from sufficiently
far outside, the Solar System is a point mass.
> There don't seem to be any other meaningful
>characteristic (such as waveshape or voltage) from the output of a
>biological neuron, just the presence or not of the pulse.
This is incorrect. What's usually regarded as more important than
the presence or absence of a pulse is the firing *rate*, measured
as a scalar quantity. Different neurons respond at different rates
depending on the circumstances, &c.
Viewed in this light, the (scalar) activation level present at
the output of an ANN unit is a model of the scalar activation level
of the output of a real neuron. In more sophisticated models, this
time course can be explicitly taken into account -- Birkbeck College,
Univ. of London and Cal-tech both have active research groups looking
at this sort of model.
-kitten