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Extension of Yager's negation of a probability distribution based on Tsallis entropy
Authors:Jing Zhang  Ruqin Liu  Jianfeng Zhang  Bingyi Kang
Affiliation:College of Information Engineering, Northwest A&F University, Yangling, China
Abstract:The negation of probability distribution becomes an important topic since some problems are burdensome to deal with directly. Inspired by Yager's negation of probability distribution, an extension model to measure the negation of a probability distribution is proposed using the idea of a nonextensive statistic based on Tsallis entropy. Proofs show that the proposed extension of negation of probability distribution converges to the maximum Tsallis entropy. The proposed model may extend Yager's method to consider the influences of the correlations in a system, which gives the different convergent routes. Some numerical simulation results are used to illustrate the effectiveness of the proposed methodology.
Keywords:entropy  negation  probability distribution  Tsallis entropy
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