Anomaly detection is the process of identifying events or patterns that differ from expected behavior. Anomaly detection can range from simple outlier detection to complex machine learning algorithms trained to uncover hidden patterns across hundreds of signals.

Engineers and data scientists use anomaly detection to identify:

• Faults in machinery for predictive maintenance
• Defects in manufacturing production lines
• Cancer in radiology images
• Fraud in financial transactions
• Customer churn in retail
• Unusual movements in video surveillance footage

There are many ways to design anomaly detection algorithms in MATLAB®. The anomaly detection approach most suitable for a given application will depend on the amount of anomalous data available, and whether you can distinguish anomalies from normal data.