sslug-teknik team mailing list archive

[Peter Makholm <peter@xxxxxxxxxxx>]

Carsten Svaneborg <carsten.svaneborg@xxxxxxxx> writes:

> Hvordan virker det i praksis?

/usr/src/linux/drivers/char/random.c

Der er en god overordnet beskrivelse i begyndelse lige efter
licenssnasket.

> Den forstår jeg ikke. Et lukket system vil have en tilstand med
> (endelig) maksimal entropi nemmelig ligevægtstilstanden ifølge
> termodynamik. Så der er jeg helt enig.

Der er forskel på det datalogiske entropibegreb og det fysiske
entropibegreb. Basalt set kan det reduceres til noget der ligner
hinanden, men intuitivt modsiger de ofte sig selv.

Stinson skriver i "Cryptography, Theory and Practise" følgende
indledende bemærkninger om entropi:

  The basic tool in studying this question is the idea of entropy, a
  concept from information theory introduced by Shannon in
  1948. Entropy can be thought of as a mathematical measure of
  information or uncertainty, and is computed as a function of a
  probability distribution
  Suppose we have a random variable X which takes on a finite set of
  values according to a probability ditribution p(X). What is the
  information gained by an event which takes place according to
  distribution p(X)? Equivalently, if the event has not (yet) taken
  place, what is the uncertainty about the outcome? This quantity is
  called the entropy of X and is denoted by H(X).

-- 
Peter