 Statistical signal processing

Statistical signal processing is a field that combines principles of statistics and signal processing to analyze and interpret signals that are subject to noise and uncertainty. It focuses on developing algorithms and methodologies to extract meaningful information from noisy or incomplete data. Here are some key aspects of statistical signal processing: 1. **Modeling Signals and Noise**: In statistical signal processing, signals are often modeled as random processes.