A Graduated Pair-Symbol Numerical Encoding Framework for ROM Optimization and High-Throughput Network Transmission

The Graduated Numerical Encoding System (GNES) is a mathematical and engineering architecture designed to compress and transmit high-precision numerical data (down to 10^{-12} precision) using a fixed 4-byte (32-bit) representation reduced to a compact Quad-Byte Hexadecimal payload (e.g., 0xF43DFC3D). Key Highlights & Benefits Zero-Loss Reversibility: Mathematically proven lossless recovery with zero residual error, verified through an automated $1,000,000$-sample stress test. ROM Hardware Optimization: Cuts silicon area and reduces dynamic power consumption by 46.5% using a 16-LUT Verilog hardware decoder with a 1.12\text{ ns}$ propagation delay. Network Transmission Acceleration: Decreases numerical payload size by 50% to 71.4%, significantly optimizing bandwidth usage and router processing speeds across 5G/6G networks.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-26
DOI
https://doi.org/10.5281/zenodo.23667145
Primary Topic
Numerical Methods and Algorithms
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

A Graduated Pair-Symbol Numerical Encoding Framework for ROM Optimization and High-Throughput Network Transmission

Almodiny Mohammed
Zenodo (CERN European Organization for Nuclear Research)
Numerical Methods and Algorithms
preprint

A Graduated Pair-Symbol Numerical Encoding Framework for ROM Optimization and High-Throughput Network Transmission

Almodiny Mohammed
preprint en

Abstract

The Graduated Numerical Encoding System (GNES) is a mathematical and engineering architecture designed to compress and transmit high-precision numerical data (down to 10^{-12} precision) using a fixed 4-byte (32-bit) representation reduced to a compact Quad-Byte Hexadecimal payload (e.g., 0xF43DFC3D). Key Highlights & Benefits Zero-Loss Reversibility: Mathematically proven lossless recovery with zero residual error, verified through an automated $1,000,000$-sample stress test. ROM Hardware Optimization: Cuts silicon area and reduces dynamic power consumption by 46.5% using a 16-LUT Verilog hardware decoder with a 1.12\text{ ns}$ propagation delay. Network Transmission Acceleration: Decreases numerical payload size by 50% to 71.4%, significantly optimizing bandwidth usage and router processing speeds across 5G/6G networks.

Zenodo (CERN European Organization for Nuclear Research)
Numerical Methods and Algorithms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon