Explorerโ€บMathematicsโ€บMathematics
Research PaperResearchia:202604.06025

High-Dimensional Signal Compression: Lattice Point Bounds and Metric Entropy

A. Iosevich

Abstract

We study worst-case signal compression under an $\ell^2$ energy constraint, with coordinate-dependent quantization precisions. The compression problem is reduced to counting lattice points in a diagonal ellipsoid. Under balanced precision profiles, we obtain explicit, dimension-dependent upper bounds on the logarithmic codebook size. The analysis refines Landau's classical lattice point estimates using uniform Bessel bounds due to Olenko and explicit Abel summation. --- Source: arXiv:2604.03178v...

Submitted: April 6, 2026Subjects: Mathematics; Mathematics

Description / Details

We study worst-case signal compression under an โ„“2\ell^2 energy constraint, with coordinate-dependent quantization precisions. The compression problem is reduced to counting lattice points in a diagonal ellipsoid. Under balanced precision profiles, we obtain explicit, dimension-dependent upper bounds on the logarithmic codebook size. The analysis refines Landau's classical lattice point estimates using uniform Bessel bounds due to Olenko and explicit Abel summation.


Source: arXiv:2604.03178v1 - http://arxiv.org/abs/2604.03178v1 PDF: https://arxiv.org/pdf/2604.03178v1 Original Link: http://arxiv.org/abs/2604.03178v1

Please sign in to join the discussion.

No comments yet. Be the first to share your thoughts!

Access Paper
View Source PDF
Submission Info
Date:
Apr 6, 2026
Topic:
Mathematics
Area:
Mathematics
Comments:
0
Bookmark
High-Dimensional Signal Compression: Lattice Point Bounds and Metric Entropy | Researchia