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Data · dataset · 2026

Simulation Data and Code for Exponential-History Covariance Compression for Grünwald–Letnikov Filtering

Listed in Teesside University Research Data Repository

This dataset provides Python code, simulation inputs and numerical results supporting “Exponential-History Covariance Compression for Grünwald–Letnikov Filtering”.

Description

It includes the seven-method comparison, full-precision system models and exponential poles, and the 18-system four-policy ablation. See README.md for installation, reproduction commands and validation scope.

Some historical kernel-check inputs and the original timing environment are unavailable; the package does not support complete reproduction of every historical experiment.

Links

Where it is published

Catalogue records · 1

Topics

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Simulation 75%
Provenance · 1 source records, 7 field assertions
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Teesside University Research Data Repositoryoai:data.mendeley.com/mrxdhzjh4p.117 h agoJSON v1
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