The PB-CUDSA algorithm deterministically classifies system states as coherent, marginal, unstable, or collapsing by measuring relative drift between successive states.
Introduces a unified deterministic algorithm for classifying dynamical stability across various complex systems.
Absolute Event Rate: 0% vs 0%
Early failure in biological, physical, and complex systems often occurs despite apparently normal structure or functionality, indicating underlying dynamical instability. This document introduces a unified deterministic algorithm that combines Predictive Bioharmonics (PB) and the Complete Unified Drift Saturation Architecture (CUDSA) into a single framework for classifying dynamical stability versus instability. The PB–CUDSA algorithm evaluates system evolution by measuring relative drift between successive states and saturating drift channels into a coherent stability signal. It operates without probabilities, learning, tuning, optimization, or domain-specific assumptions, and deterministically classifies system states as coherent, marginal, unstable, or collapsing based solely on dynamical structure. The core algorithm is defined independent of application domain; fertility, disease, climate, mechanical systems, and other uses are non-limiting implementations of the same signal.
Tess Fries (Mon,) reported a other. The PB-CUDSA algorithm deterministically classifies system states as coherent, marginal, unstable, or collapsing by measuring relative drift between successive states.