DocumentCode
2635787
Title
On exponential entropies
Author
Kvålseth, Tarald O.
Author_Institution
Dept. of Mech. Eng., Minnesota Univ., Minneapolis, MN, USA
Volume
4
fYear
2000
fDate
2000
Firstpage
2822
Abstract
As a number of information, an entropy has been defined as the weighted mean of a set of exponential functions involving the probabilities of a set of random events. The exponential entropy is claimed to have certain advantages over the classical Shannon entropy (C.E. Shannon, 1948). The article proposes two different generalizations of the exponential entropy, each of which represents a one-parameter generalization. Shannon´s entropy is shown to be a particular member of one of these two new families of information measures. Some of the important properties of the new measures are discussed
Keywords
computational complexity; entropy; probability; classical Shannon entropy; exponential entropies; exponential functions; information measures; one-parameter generalization; random events; weighted mean; Entropy; Image processing; Measurement units; Mechanical engineering; Particle measurements; Probability distribution; Upper bound;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 2000 IEEE International Conference on
Conference_Location
Nashville, TN
ISSN
1062-922X
Print_ISBN
0-7803-6583-6
Type
conf
DOI
10.1109/ICSMC.2000.884425
Filename
884425
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