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From: meron@cars3.uchicago.edu
Subject: Re: Neural Nets and Quantum Mechanics/Computation
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References: <31FFD52A.6339@axon.cs.byu.edu> <290598840wnr@chmqst.demon.co.uk> <320909B7.5DA5@axon.cs.byu.edu> <320BCE4A.101C@citicorp.com>
Date: Fri, 9 Aug 1996 22:30:27 GMT
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Xref: glinda.oz.cs.cmu.edu comp.ai.neural-nets:32933 sci.physics:206150

In article <320BCE4A.101C@citicorp.com>, Robert Fung <robert.fung@citicorp.com> writes:
>
>    In Digital Signal Processing, conversion is done from a 
>    "continuous" function to a discrete function. The Nyquist
>    limit is DSP's Uncertainty Principle since there are many 
>    discrete  possibilities for a given continuous function.
>
It is the other way around.  There are many (an infinity, in fact) 
continuous functions corresponding to a given set of discrete values.

>    In QM on the other end, the problem is you have discrete 
>    functions and Heisenberg's uncertainty rules there.

Who said that in QM you've discrete functions?

Mati Meron			| "When you argue with a fool,
meron@cars.uchicago.edu		|  chances are he is doing just the same"
