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papersSEP 10 04:00 UTC

PeriodicCALM: real-time anomaly detection for cyclostationary data streams

A new arXiv preprint presents PeriodicCALM, a framework for detecting anomalies on the fly in cyclostationary data streams, whose statistical properties vary periodically over time. Rather than relying on classical stationary assumptions, the algorithm adapts to these recurring temporal patterns as it monitors live data for deviations. The work was posted to arXiv's machine learning listing as a cross-listed submission.

arXivPeriodicCALManomaly detectioncyclostationary data streamsreal-time anomaly detection

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