Which numerical method is commonly used to process digital signals?

The Fourier Transform is a fundamental numerical method widely utilized in digital signal processing. It transforms a time-domain signal into its frequency-domain representation, allowing for the analysis of the frequency components present in the signal. This is particularly important in fields like audio processing, telecommunications, and image analysis. By using the Fourier Transform, engineers and researchers can identify patterns, filter signals, and perform various analyses that are essential for the effective manipulation and understanding of digital signals.

The other methods listed have different applications; for instance, Newton's Method is typically used for finding roots of equations, Gradient Descent is an optimization algorithm primarily used in machine learning and statistics, and Monte Carlo Simulation is a technique used for modeling and understanding uncertainty in various systems. While these methods are crucial in their respective fields, they do not serve the same purpose as the Fourier Transform in the context of digital signal processing.