Conditional constrained and unconstrained quantization for probability distributions

Authors

Megha Pandey
Mrinal Kanti Roychowdhury, The University of Texas Rio Grande Valley

Document Type

Article

Publication Date

2024

Abstract

In this paper, we present the idea of conditional quantization for a Borel probability measure P on a normed space Rk. We introduce the concept of conditional quantization in both constrained and unconstrained scenarios, along with defining the conditional quantization errors, dimensions, and coefficients in each case. We then calculate these values for specific probability distributions. Additionally, we demonstrate that for a Borel probability measure, the lower and upper quantization dimensions and coefficients do not depend on the conditional set of the conditional quantization in both constrained and unconstrained quantization.

Recommended Citation

Pandey, Megha, and Mrinal Kanti Roychowdhury. "Conditional constrained and unconstrained quantization for probability distributions." arXiv e-prints (2023): arXiv-2312.