Quantization for a probability distribution generated by an infinite iterated function system

Authors

Lakshmi Roychowdhury, The University of Texas Rio Grande Valley
Mrinal Kanti Roychowdhury, The University of Texas Rio Grande Valley

Document Type

Article

Publication Date

5-24-2022

Abstract

Quantization for probability distributions concerns the best approximation of a d-dimensional probability distribution P by a discrete probability with a given number n of supporting points. In this paper, we have considered a probability measure generated by an infinite iterated function system associated with a probability vector on R. For such a probability measure P , an induction formula to determine the optimal sets of n-means and the nth quantization error for every natural number n is given. In addition, using the induction formula we give some results and observations about the optimal sets of n-means for all n ≥ 2

Comments

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Recommended Citation

Roychowdhury, Lakshmi, and Mrinal Kanti Roychowdhury. 2022. “Quantization for a Probability Distribution Generated by an Infinite Iterated Function System.” Communications of the Korean Mathematical Society 37 (3): 765–800. https://doi.org/10.4134/CKMS.c210266.

Creative Commons License

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

Publication Title

Commun. Korean Math. Soc.

DOI

10.4134/CKMS.c210266