shift invariance

[rolf@cs.rug.nl]

Dear Jerry,

a short comment regarding your posting. It is no wonder that you have
not seen a proof because it is simply not true that neural networks
cannot do shift invariant recognition (SIR). If SIR is formalized it
is most probably a computable function and ANNs can at least
approximate all computable functions. No problem on a fundamental
level here. K. Fukushima has shown a long time ago that a network can
be wired up to do it.

Nevertheless, invariant recognition seems to be a fundamental property
of the visual system. It is not a _natural_ property of ANNs in the
sense that you just give them a lot of natural stimuli and they
develop the capability on their own. That, of course, makes one think
if ANNs are a good model of the visual system, or if there is still
a major point missing.

I do not quite know what to make of your remark about ``theories
overly dependent on learning''. If you have a better concept to offer
than learning from experience I will be glad to hear about it. OK, you
can say that there is ingenious machinery that does it, and the wiring
is done by the genetic code, and we can go on and think about
different things, but I do not consider that satisfactory explanation.

I am looking forward to a discussion on the topic.

Rolf

+---------------------------------------------------------------------------+
| Rolf P. W"urtz | mailto:rolf at cs.rug.nl | URL: http://www.cs.rug.nl/~rolf/ |
| Department of Computing Science, University of Groningen, The Netherlands |
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