A SYMMETRIC INFORMATION MEASURE AND INNOVATIVE BOUNDS IN THE THEORY OF COMMUNICATION SYSTEM
Neetu Choudhary1, Nihal Singh1, Devendra Singh1, Ram Surat Chauhan2, Manish Kumar Bansal2
1Faculty of Basic, Life and Applied Sciences, Apex University Jaipur- 302020, Rajasthan, India
2Department of Mathematics, Jaypee Institute of Information Technology, Noida 201309, Uttar Pradesh, India
Abstract: A non-parametric theory-based innovative symmetric information divergence measure for communication systems is proposed. This information measure belongs to the family of f-divergence. Furthermore, for the first time, we derive some bounds i.e. equalities and inequalities for this information divergence measure with well-known divergence measures, namely: Symmetric Chi-Square divergence Measure, Kumar & Johnson divergence and Bhattacharyya information measure, based on two distinct discrete probability distributions
2020 Mathematics Subject Classification: 94A05; 94A17; 26D15.
Keywords and Phrases: Communication system, non-parametric divergence measure, Symmetric Chi-Square divergence Measure, Csiszár’s f-divergence, Arithmetic mean divergence, Triangular discrimination.