SOURCE-LINKED INTELLIGENCE

Real-time and adaptive anomaly detection algorithm for cyclostationary models

arXiv · AI, language, vision and robotics · article · Sep 8, 2026 · UTC

This article introduces PeriodicCALM, an effective real-time anomaly detection framework designed for cyclostationary data streams. While classical cyclostationary processes feature periodically time-varying statistical properties, real-world signals often contain recurring impulsive components that conceal abnormal behavior. Existing real-time methods for struggle with these dynamics, frequently misinterpreting phase-dependent variability as non-cyclic anomalies and causing excessive false alarms. To address this, PeriodicCALM incorporates cycle-dependent variability to systematically ignore

Read original source ↗ Open in workspace

recordType

paper

region

Global