View source for Information theory (nonfiction)

'''Information theory''' studies the quantification, storage, and communication of information.

It was originally proposed by [[Claude Shannon (nonfiction)|Claude Shannon]] in 1948 to find fundamental limits on signal processing and communication operations such as data compression, in a landmark paper entitled "A Mathematical Theory of Communication".

The field is at the intersection of [[Mathematics (nonfiction)|mathematics]], statistics, [[Computer science (nonfiction)|computer science]], [[Physics (nonfiction)|physics]], neurobiology, and electrical engineering.

A key measure in information theory is entropy. Entropy quantifies the amount of uncertainty involved in the value of a random variable or the outcome of a random process. For example, identifying the outcome of a fair coin flip (with two equally likely outcomes) provides less information (lower entropy) than specifying the outcome from a roll of a die (with six equally likely outcomes).

== In the News ==

<gallery mode="traditional">
File:Maxwell's_demon.svg|link=Maxwell's demon (nonfiction)|[[Maxwell's demon (nonfiction)|Maxwell's demon]] not so bad once you get to know [[Mathematics|the math]], says [[Léon Brillouin (nonfiction)|Brillouin]].
</gallery>

== Fiction cross-reference ==

* [[Crimes against mathematical constants]]

== Nonfiction cross-reference ==

* [[Claude Shannon (nonfiction)]]
* [[Alan Turing (nonfiction)]]

External links:

* [https://en.wikipedia.org/wiki/Information_theory Information theory] @ Wikipedia

[[Category:Nonfiction (nonfiction)]]
[[Category:Information theory (nonfiction)]]
[[Category:Mathematics (nonfiction)]]