enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Information theory - Wikipedia

    en.wikipedia.org/wiki/Information_theory

    In this context, either an information-theoretical measure, such as functional clusters (Gerald Edelman and Giulio Tononi's functional clustering model and dynamic core hypothesis (DCH) [47]) or effective information (Tononi's integrated information theory (IIT) of consciousness [48] [49] [50]), is defined (on the basis of a reentrant process ...

  3. Information theory and measure theory - Wikipedia

    en.wikipedia.org/wiki/Information_theory_and...

    Many of the concepts in information theory have separate definitions and formulas for continuous and discrete cases. For example, entropy is usually defined for discrete random variables, whereas for continuous random variables the related concept of differential entropy, written (), is used (see Cover and Thomas, 2006, chapter 8).

  4. Edwin Thompson Jaynes - Wikipedia

    en.wikipedia.org/wiki/Edwin_Thompson_Jaynes

    Jaynes around 1982. Edwin Thompson Jaynes (July 5, 1922 – April 30, [1] 1998) was the Wayman Crow Distinguished Professor of Physics at Washington University in St. Louis.He wrote extensively on statistical mechanics and on foundations of probability and statistical inference, initiating in 1957 the maximum entropy interpretation of thermodynamics [2] [3] as being a particular application of ...

  5. Entropy (information theory) - Wikipedia

    en.wikipedia.org/wiki/Entropy_(information_theory)

    In the view of Jaynes (1957), [20] thermodynamic entropy, as explained by statistical mechanics, should be seen as an application of Shannon's information theory: the thermodynamic entropy is interpreted as being proportional to the amount of further Shannon information needed to define the detailed microscopic state of the system, that remains ...

  6. Shannon's source coding theorem - Wikipedia

    en.wikipedia.org/wiki/Shannon's_source_coding...

    In information theory, the source coding theorem (Shannon 1948) [2] informally states that (MacKay 2003, pg. 81, [3] Cover 2006, Chapter 5 [4]): N i.i.d. random variables each with entropy H(X) can be compressed into more than N H(X) bits with negligible risk of information loss, as N → ∞; but conversely, if they are compressed into fewer than N H(X) bits it is virtually certain that ...

  7. Information-theoretic security - Wikipedia

    en.wikipedia.org/wiki/Information-theoretic_security

    One paper by Negi and Goel details its implementation, and Khisti and Wornell computed the secrecy capacity when only statistics about Eve's channel are known. [12] [13] Parallel to that work in the information theory community is work in the antenna community, which has been termed near-field direct antenna modulation or directional modulation ...

  8. Entropy in thermodynamics and information theory - Wikipedia

    en.wikipedia.org/wiki/Entropy_in_thermodynamics...

    Despite the foregoing, there is a difference between the two quantities. The information entropy Η can be calculated for any probability distribution (if the "message" is taken to be that the event i which had probability p i occurred, out of the space of the events possible), while the thermodynamic entropy S refers to thermodynamic probabilities p i specifically.

  9. Asymptotic equipartition property - Wikipedia

    en.wikipedia.org/wiki/Asymptotic_equipartition...

    Given a discrete-time stationary ergodic stochastic process on the probability space (,,), the asymptotic equipartition property is an assertion that, almost surely, ⁡ (,, …,) where () or simply denotes the entropy rate of , which must exist for all discrete-time stationary processes including the ergodic ones.