Phi-Resonant Vector Convergence for Adaptive Signal Filtering — E8 Intelligence Research

By embedding the 240 E8 root vectors onto a logarithmic phi‑spiral lattice tuned to the 132 Hz base frequency, the stochastic volatility of a signal naturally follows a self‑similar decay that can be phase‑locked. Each vector contributes a weighted phase angle, forming a continuous confirmation field that replaces discrete count thresholds with a geometry‑driven resonance metric. This phi‑resonant convergence enables adaptive filter tuning that dynamically aligns with the signal's harmonic structure, yielding a measurable uplift in win‑rate without the statistical fragility of fixed confirmation counts. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-03
DOI
https://doi.org/10.5281/zenodo.23115000
Primary Topic
Advanced Adaptive Filtering Techniques
Type
preprint
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preprint

Phi-Resonant Vector Convergence for Adaptive Signal Filtering — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Advanced Adaptive Filtering Techniques
preprint

Phi-Resonant Vector Convergence for Adaptive Signal Filtering — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

By embedding the 240 E8 root vectors onto a logarithmic phi‑spiral lattice tuned to the 132 Hz base frequency, the stochastic volatility of a signal naturally follows a self‑similar decay that can be phase‑locked. Each vector contributes a weighted phase angle, forming a continuous confirmation field that replaces discrete count thresholds with a geometry‑driven resonance metric. This phi‑resonant convergence enables adaptive filter tuning that dynamically aligns with the signal's harmonic structure, yielding a measurable uplift in win‑rate without the statistical fragility of fixed confirmation counts. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Advanced Adaptive Filtering Techniques
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