Wiener-Khinchin Theorem

S(f) = ∫ R(τ) e^{−2πifτ} dτ — power spectrum is the Fourier transform of autocorrelation

Signal Composition

Peak frequency:
ACF lag-1:
Coherence time:
SNR (dB):
Wiener-Khinchin (1930/34): for a wide-sense stationary process, the power spectral density S(f) equals the Fourier transform of the autocorrelation function R(τ) = E[x(t)x(t+τ)].

Fundamental: you don't need to compute S(f) directly — just compute R(τ) and transform it.