Re: how to find the best ADC step size?

From: Clay S. Turner (Physics_at_Bellsouth.net)
Date: 12/22/04 

Date: Wed, 22 Dec 2004 15:05:51 -0500

"Randy Yates" <randy.yates@sonyericsson.com> wrote in message
news:xxpllbqjpjf.fsf@usrts005.corpusers.net...
> "Clay S. Turner" <Physics@Bellsouth.net> writes:
>> [...]
>> The idea is to try to make each symbol contribute equally to the overall
>> process. Imagine looking at your data after a huge number of symbols was
>> received. The idea is to make the info provided by each type of symbol
>> contribute equally.
>
> But this Huffman coding won't do that. Choosing a representation for a
> symbol doesn't change the probability of the symbol occurring. It
> does, however, minize the average symbol rate - I certainly see
> that. Perhaps I'm being blind?
> --

Hello Randy,

The Huffman problem and the quantization problem are related in they both
implement methods to effectively flatten out variations. True they are
different in that the Huffman problem is trying to minimize the average
number of bits per sample and the quantization problem is trying to maximize
the information per sample. The differences arise from the constraints and
what you are starting with. In one case we have a fixed amount of
information, so how few total bits can we fit all of the info in. The
theoretical answer is the entropy, but the practical answer (comes from
requiring whole numbers of bits in a symbol is the Huffman entropy.) In the
other case we have a fixed symbol size, so how can we get the most info per
symbol. The connection is the entropy and its maximization requires a flat
distribution.

In Huffman coding we sort the symbol probabilities into descending order and
then we make multiple passes throught the list each time combining the two
lowest probilites together. So we are essentially trying to make each path's
probability be the same or at leat similar. In the quantization we are just
diving up the total probability into N equal regions.

You are not being blind, you are just asking how two seemingly different
things are related. And the relation is through a flattening out of the
probabilty function.

I hope this helps to clear some things up.

Clay

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