Title :
On exponential entropies
Author :
Kvålseth, Tarald O.
Author_Institution :
Dept. of Mech. Eng., Minnesota Univ., Minneapolis, MN, USA
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;
Conference_Titel :
Systems, Man, and Cybernetics, 2000 IEEE International Conference on
Conference_Location :
Nashville, TN
Print_ISBN :
0-7803-6583-6
DOI :
10.1109/ICSMC.2000.884425
