TSA AR Spectrum (Waveform) VI
- Updated2025-12-08
- 4 minute(s) read
Computes the single-sided power spectral density (PSD) of a univariate time series based on autoregressive (AR) modeling. The PSD computed with this method is exempt from window effects and has a better frequency resolution than the results from using the periodogram method.

Inputs/Outputs
frequency bins
—
frequency bins specifies the number of frequency bins for which this VI computes the single-sided power spectral density PSD. The length of the single-sided PSD is (frequency bins/2+1). The default is 1024.
Xt
—
Xt specifies the univariate time series.
AR method
—
AR method specifies the method this VI uses to estimate the autoregressive (AR) model.
AR order
—
AR order specifies the order of the autoregressive (AR) model. The value of AR order must be greater than 0. The default is 4.
error in (no error)
—
error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
dB on? (T)
—
dB on? specifies whether this VI returns the PSD in decibels or in a linear scale. If dB on? is TRUE, this VI returns the PSD in decibels. If dB on? is FALSE, this VI returns the PSD in a linear scale. The default is TRUE.
PSD
—
PSD returns information about the single-sided power spectral density (PSD).
unit
—
unit returns the engineering unit of the PSD. You can specify an engineering unit for a time series by using the TSA Scale to EU VI.
error out
—
error out contains error information. This output provides standard error out functionality. |
TSA AR Spectrum Details
This VI computes the single-sided PSD of a univariate time series based on AR modeling according to the following equation:

where S(f) is the PSD of the time series. df is the frequency interval, which is computed as fs/N. N is the number of frequency bins, fs is the sampling rate, and s² is the noise variance of the estimated AR model of the time series. a is an array that contains the coefficients of the AR model. a=[1, a1, a2,… ,an], where n is AR order. Before computing the PSD, this VI wraps a to N-point series a'.
The minimum length requirement for the input time series needs to be at least two times the AR order.
Examples
Refer to the Power Spectral Density Estimation VI in the labview\examples\Time Series Analysis\TSAGettingStarted directory for an example of using the TSA AR Spectrum VI.
frequency bins
—
Xt
—
AR method
—
error in (no error)
—
dB on? (T)
—
PSD
—
f0
—
S(f)
—
unit
—
error out
—