Title :
Minimum entropy and information measure
Author :
Yuan, Lin ; Kesavan, H.K.
Author_Institution :
Dept. of Stat., Waterloo Univ., Ont., Canada
fDate :
8/1/1998 12:00:00 AM
Abstract :
Kapur et al. (1995) introduced the MinMax information measure, which is based on both maximum and minimum entropy. The major obstacle for using this measure, in practice, is the difficulty in finding the minimum entropy. An analytical expression has already been developed for calculating the minimum entropy when only variance is specified. An analytical formula is obtained for calculating the minimum entropy when only mean is specified, and numerical examples are given for illustration
Keywords :
maximum entropy methods; minimax techniques; minimum entropy methods; MinMax information measure; analytical formula; maximum entropy; minimum entropy; variance; Analysis of variance; Design engineering; Entropy; Equations; Information theory; Measurement uncertainty; Minimax techniques; Probability distribution; Statistical distributions; Systems engineering and theory;
Journal_Title :
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
DOI :
10.1109/5326.704595
