Linear code-based vector quantization for independent random variables
Boris Kudryashov, Kirill Yurkov
TL;DR
This paper investigates the limits of data compression for independent random variables using linear codes over finite fields, focusing on the achievable rate-distortion function.
Contribution
It provides a theoretical analysis of the rate-distortion function for linear code-based vector quantization of independent variables.
Findings
Derived the rate-distortion function R(D) for linear codes over GF(q)
Identified conditions under which linear codes achieve optimal compression
Extended understanding of vector quantization limits for independent variables
Abstract
In this paper we analyze the rate-distortion function R(D) achievable using linear codes over GF(q), where q is a prime number.
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Taxonomy
TopicsAdvanced Data Compression Techniques · Error Correcting Code Techniques · Advanced Wireless Communication Techniques