A NEW EXPONENTIAL DIRECTED DIVERGENCE INFORMATION MEASURE
K. C. Jain, Praphull Chhabra
Abstract
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K. C. Jain, Praphull Chhabra
Abstract
Open-access reader
Depending upon the nature of the problem, different divergence measures are suitable. So it is always desirable to develop a new divergence measure. In the present work, new information divergence measure, which is exponential in nature, is introduced and characterized. Bounds of this new measure are obtained in terms of various symmetric and non- symmetric measures together with numerical verification by using two discrete distributions: Binomial and Poisson. Fuzzy information measure and Useful information measure corresponding to new exponential divergence measure are also introduced.
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Depending upon the nature of the problem, different divergence measures are suitable. So it is always desirable to develop a new divergence measure. In the present work, new information divergence measure, which is exponential in nature, is introduced and characterized. Bounds of this new measure are obtained in terms of various symmetric and non- symmetric measures together with numerical verification by using two discrete distributions: Binomial and Poisson. Fuzzy information measure and Useful information measure corresponding to new exponential divergence measure are also introduced.
Key concepts: Measure (data warehouse), Divergence (linguistics), Exponential family, Exponential function, Mathematics, Applied mathematics, Kullback–Leibler divergence, Discrete measure