Consider the well known power spectral density and the signal auto-correlation function in the case of a stationary process.

Specific applications may be concerned with changes in the mean, variance, correlation, or spectral density of the process.

Also, we are defining the power spectral densities as follows:

Second, the sample spectrum which deviates from the assumed spectral density is another one.

The spectral density of these switching waveforms has energy concentrated at relatively high frequencies.

The noise power spectral density in the frequency range of interest.

The value of the energy spectral density at is then estimated to be .

More generally, similar techniques may be used to estimate a time-varying spectral density.

Most "frequency" graphs really display only the spectral density.

The periodogram is an estimate of the spectral density of a signal.