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Main Authors: Doubchak, Ariel, Philosof, Tal, Erez, Uri, Berman, Amit
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2409.06839
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author Doubchak, Ariel
Philosof, Tal
Erez, Uri
Berman, Amit
author_facet Doubchak, Ariel
Philosof, Tal
Erez, Uri
Berman, Amit
contents We address the problem of indirect quantization of a source subject to a mean-squared error distortion constraint. A well-known result of Wolf and Ziv is that the problem can be reduced to a standard (direct) quantization problem via a two-step approach: first apply the conditional expectation estimator, obtaining a ``new'' source, then solve for the optimal quantizer for the latter source. When quantization is implemented in hardware, however, invariably constraints on the allowable class of quantizers are imposed, typically limiting the class to \emph{time-invariant} scalar quantizers with contiguous quantization cells. In the present work, optimal indirect quantization subject to these constraints is considered. Necessary conditions an optimal quantizer within this class must satisfy are derived, in the form of generalized Lloyd-Max conditions, and an iterative algorithm for the design of such quantizers is proposed. Furthermore, for the case of a scalar observation, we derive a non-iterative algorithm for finding the optimal indirect quantizer based on dynamic programming.
format Preprint
id arxiv_https___arxiv_org_abs_2409_06839
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Design of Threshold-Constrained Indirect Quantizers
Doubchak, Ariel
Philosof, Tal
Erez, Uri
Berman, Amit
Information Theory
We address the problem of indirect quantization of a source subject to a mean-squared error distortion constraint. A well-known result of Wolf and Ziv is that the problem can be reduced to a standard (direct) quantization problem via a two-step approach: first apply the conditional expectation estimator, obtaining a ``new'' source, then solve for the optimal quantizer for the latter source. When quantization is implemented in hardware, however, invariably constraints on the allowable class of quantizers are imposed, typically limiting the class to \emph{time-invariant} scalar quantizers with contiguous quantization cells. In the present work, optimal indirect quantization subject to these constraints is considered. Necessary conditions an optimal quantizer within this class must satisfy are derived, in the form of generalized Lloyd-Max conditions, and an iterative algorithm for the design of such quantizers is proposed. Furthermore, for the case of a scalar observation, we derive a non-iterative algorithm for finding the optimal indirect quantizer based on dynamic programming.
title Design of Threshold-Constrained Indirect Quantizers
topic Information Theory
url https://arxiv.org/abs/2409.06839