Two New Parametric Entropic Models for Discrete Probability Distributions
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Abstract
Information theory fundamentally deals with two types of theoretical models frequently well acknowledged as entropy and divergence. In the literature of entropy models for the discrete probability distributions, there survive numerous standard models but still there is possibility that several innovative models can be constructed so as to provide their applications in a variety of disciplines of mathematical sciences. The present communication is a right step in this direction and participates with the derivation of two new parametric models of entropy. Furthermore, it provides the meticulous study of the most advantageous properties of the projected discrete models to prove their legitimacy.
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