Understanding how signals correlate as they slide past each other
Cross-correlation is a measure of similarity between two signals as a function of the displacement (lag) of one relative to the other. It's commonly used in signal processing, pattern recognition, and time series analysis to find patterns, delays, or similarities between signals.
1. The red signal (Signal 1) remains stationary while the blue signal (Signal 2) slides across it.
2. At each position (lag), we multiply corresponding values and sum them up.
3. The result shows how well the signals match at each lag position.
4. A high correlation value indicates the signals are similar at that lag.
• Finding time delays between signals (e.g., echo detection)
• Pattern matching in images and audio
• Synchronizing signals in communications
• Detecting periodicities in time series data