Wiener-Khinchin theorem

The Wiener-Khinchin theorem states that the power spectral density of a stationary random process (how the signal's power is distributed across frequencies) can be obtained by taking the Fourier transform of its autocorrelation function (a measure of how the signal correlates with itself over time). In simpler terms, it connects the signal's time-based behavior with its frequency content: analyzing how the signal correlates over time allows us to understand its frequency components, and vice versa. This relationship is fundamental in signal processing and helps analyze signals in various fields such as communications and engineering.