Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
393194 | Information Sciences | 2012 | 8 Pages |
Abstract
ross-entropy is a measure of the difference between two distribution functions. In order to deal with the divergence of uncertain variables via uncertainty distributions, this paper aims at introducing the concept of cross-entropy for uncertain variables based on uncertain theory, as well as investigating some mathematical properties of this concept. Several practical examples are also provided to calculate uncertain cross-entropy. Furthermore, the minimum cross-entropy principle is proposed in this paper. Finally, a study of generalized cross-entropy for uncertain variables is carried out.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Xiaowei Chen, Samarjit Kar, Dan A. Ralescu,