Quantifies how the power of a stationary [[Stochastic Processes|random process]] is distributed across frequencies. --- Given a square-integrable [[Maps and Induced Structures - Functions, Pushforwards and Pullbacks|function]] $f(t)$ with [[Fourier Series and Transform|Fourier Transform]] $\mathcal{F}\{f(t))\}=\hat{f}(\omega)$, the PSD is defined as$S_t(f)=|\hat{f}(\omega)|^{2}$ For discrete-time signals $x[n]$ with sampling frequency $f_s$, the PSD is [[Statistic and Estimator|estimated]] via $S_x(\frac{k}{N}f_s)=\frac{1}{N}|X[k]|^{2}$