Standard signal analysis methods characterise signals primarily through amplitude, frequency content, and statistical distribution. These representations are not designed to capture whether a signal reflects a structurally coherent underlying process. This paper presents the Vibration Depth Index (VDI), a domain-agnostic measurement instrument designed to quantify a structural property of signals distinct from amplitude and frequency. VDI is defined explicitly as an instrument rather than a predictive model or analytical framework. Three independent empirical validations are reported: (1) pre-ictal state detection in scalp EEG recordings using the CHB-MIT dataset; (2) early mechanical bearing fault detection using the CWRU Bearing Data Center dataset; (3) structural anomaly detection in network traffic using the UNSW-NB15 dataset, achieving 99.8% alert reduction at zero false positives and zero false negatives. Core computational mechanisms are proprietary and are not disclosed in this paper.
Kanan Rzayev (Sat,) studied this question.