Guy Hoelzer  wrote or quoted:
> in article chnea4$30dh$1{at}darwin.ediacara.org, Tim Tyler at tim{at}tt1lock.org

> > Shannon's information has proved to be a remarkably useful construct -
> > AFAICS.
> 
> It has indeed.  Indeed, I often rely on it myself.  However, my use of the
> Shannon/Weaver information measure (-p_i x log p_i,) and most usage in the
> literature utterly ignores the role of perception because it has no
> representation in the equation.  In fact, the equation is solely about the
> degree of structure in the data.

p_i is the probability of symbol i arising at that point.

Different observers will make different estimates of that -
based on their past experiences.

An observer who knows what symbol is coming next (because he
has seen a very similar message before) will assign different
probabilites to the symbols from an observer who is seeing
the message for the first time - and both will assign different
probabilities from an observer who is not even familiar with
the language the message is written in.

There is no such thing as probabilty independent of an observer -
probability is fundamentally a measure of an observer's uncertainty
about the course of events.
-- 
__________
 |im |yler  http://timtyler.org/  tim{at}tt1lock.org  Remove lock to reply.
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