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New entropy bounds via uniformly convex functions

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  • Sayyari, Yamin

Abstract

In this paper we give extensions of Jensen’s discrete inequality considering the class of uniformly convex functions. We also introduce lower and upper bounds for Jensen’s inequality (for uniformly convex functions), and we apply this results in information theory and obtain new and strong bounds for Shannon’s entropy of a probability distribution.

Suggested Citation

  • Sayyari, Yamin, 2020. "New entropy bounds via uniformly convex functions," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
  • Handle: RePEc:eee:chsofr:v:141:y:2020:i:c:s0960077920307554
    DOI: 10.1016/j.chaos.2020.110360
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    Cited by:

    1. Rasheed, T. & Butt, S.I. & Pečarić, Đ. & Pečarić, J., 2022. "Generalized cyclic Jensen and information inequalities," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).
    2. Sayyari, Yamin & Dehghanian, Mehdi, 2024. "A new class of convex functions and applications in entropy and analysis," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).

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