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

Description

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

Steps to reproduce

Extract the ZIP and read README.md. python -m pip install -r requirements.txt python code/check_results.py

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