Peak Detection in Signal Processing

Peak detection in signal processing represents a fundamental technique for identifying local maxima (peaks) or minima (valleys) within signal data. By implementing peak detection algorithms, engineers can precisely locate extremum points in signals with both speed and accuracy. This capability proves essential across numerous applications including audio processing (for note onset detection), image processing (for edge detection), and video analysis (for motion event identification). The algorithm typically involves signal preprocessing (smoothing/noise reduction), followed by threshold-based peak identification where signal values exceed neighboring points by a specified margin. Key implementation considerations include selecting appropriate window sizes for local comparison and setting adaptive thresholds to handle varying signal amplitudes. This documentation includes a fully functional demo that can be executed directly to observe the peak detection algorithm's operation on sample signals. The demo showcases real-time peak marking, threshold visualization, and performance metrics calculation. We hope this resource provides valuable insights into practical peak detection implementation!