Bounds of Mean Code Word Lenth With Generalized Information Measure and its Application in Coding Theory


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Authors

  • Litegebe Wondie Department of Mathematics, College of Natural and Computational Science, University of Gondar, Gondar, Ethiopia
  • Satish Kumar Department of mathematics, Maharishi Markandeshwar (Deemed to be) University, Mullana, Ambala, Haryana, India

Keywords:

Shannon inequality, Tsalli's entropy, Codeword length, Kraft inequality

Abstract

In this communication, we find a lower and upper bounds for mean code word length for complete and incomplete probability distribution with generalized information measure and we identify its application in coding theory.

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Published

15-09-2019

How to Cite

Litegebe Wondie, & Satish Kumar. (2019). Bounds of Mean Code Word Lenth With Generalized Information Measure and its Application in Coding Theory. International Journal of Mathematics And Its Applications, 7(3), 111–117. Retrieved from https://ijmaa.in/index.php/ijmaa/article/view/235

Issue

Vol. 7 No. 3 (2019)

Section

Research Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.