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Generalized information theory

Generalized information theory Provides an overview of major developments pertaining to generalized information theory during the lifetime of Kybernetes. Generalized information theory is viewed as a collection of concepts, theorems, principles, and methods for dealing with problems involving uncertainty‐based information that are beyond the narrow scope of classical information theory. Introduces well‐justified measures of uncertainty in fuzzy set theory, possibility theory, and Dempster‐Shafer theory. Shows how these measures are connected with the classical Hartley measure and Shannon entropy. Discusses basic issues regarding some principles of generalized uncertainty‐based information. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Kybernetes Emerald Publishing

Generalized information theory

Kybernetes , Volume 25 (7/8): 18 – Oct 1, 1996

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Publisher
Emerald Publishing
Copyright
Copyright © 1996 MCB UP Ltd. All rights reserved.
ISSN
0368-492X
DOI
10.1108/03684929610149657
Publisher site
See Article on Publisher Site

Abstract

Provides an overview of major developments pertaining to generalized information theory during the lifetime of Kybernetes. Generalized information theory is viewed as a collection of concepts, theorems, principles, and methods for dealing with problems involving uncertainty‐based information that are beyond the narrow scope of classical information theory. Introduces well‐justified measures of uncertainty in fuzzy set theory, possibility theory, and Dempster‐Shafer theory. Shows how these measures are connected with the classical Hartley measure and Shannon entropy. Discusses basic issues regarding some principles of generalized uncertainty‐based information.

Journal

KybernetesEmerald Publishing

Published: Oct 1, 1996

Keywords: Fuzzy sets; Information; Uncertainty

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