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
- Andrew Stewart Caldin
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-03
- DOI
- https://doi.org/10.5281/zenodo.23114999
- Primary Topic
- Advanced Adaptive Filtering Techniques
- Type
- preprint