| Uncertainty-Based Information: Elements of Generalized Information Theory Corr. 1999 Edition Contributor(s): Klir, George J. (Author), Wierman, Mark J. (Author) |
|
 |
ISBN: 3790812420 ISBN-13: 9783790812428 Publisher: Physica-Verlag OUR PRICE: $104.49 Product Type: Hardcover - Other Formats Published: October 1999 Annotation: The book is an overview of the development of basic ideas and mathematical results regarding measures and principles of uncertainty-based information formalized within the framework of classical set theory, probability theory, fuzzy set theory, possibility theory, and the Dempster-Shafer theory of evidence. The book contains many new results, which had until now not been available in a single monograph. The book is very useful for researchers, but it can also be used as a graduate text. |
| Additional Information |
| BISAC Categories: - Mathematics | Logic - Medical - Computers | Information Theory |
| Dewey: 003.54 |
| LCCN: 99051993 |
| Series: Studies in Fuzziness and Soft Computing |
| Physical Information: 0.5" H x 6.14" W x 9.21" (1.00 lbs) 168 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: Information is precious. It reduces our uncertainty in making decisions. Knowledge about the outcome of an uncertain event gives the possessor an advantage. It changes the course of lives, nations, and history itself. Information is the food of Maxwell's demon. His power comes from know- ing which particles are hot and which particles are cold. His existence was paradoxical to classical physics and only the realization that information too was a source of power led to his taming. Information has recently become a commodity, traded and sold like or- ange juice or hog bellies. Colleges give degrees in information science and information management. Technology of the computer age has provided access to information in overwhelming quantity. Information has become something worth studying in its own right. The purpose of this volume is to introduce key developments and results in the area of generalized information theory, a theory that deals with uncertainty-based information within mathematical frameworks that are broader than classical set theory and probability theory. The volume is organized as follows. |