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.


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Inputs/Outputs

  • cdbl.png sampling rate —

    sampling rate specifies the sampling rate, in hertz, of the univariate time series Xt. The default is 1.

  • ci32.png 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.

  • c1ddbl.png Xt —

    Xt specifies the univariate time series.

  • cu16.png AR method —

    AR method specifies the method this VI uses to estimate the autoregressive (AR) model.

  • ci32.png 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.

  • cerrcodeclst.png error in (no error) —

    error in describes error conditions that occur before this node runs. This input provides standard error in functionality.

  • cbool.png 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.

  • icclst.png PSD —

    PSD returns information about the single-sided power spectral density (PSD).

  • idbl.png f0 —

    f0 returns the lower boundary, in hertz, of the frequency range.

  • idbl.png df —

    df returns the frequency increment, in hertz.

  • i1ddbl.png S(f) —

    S(f) returns the magnitude of the PSD at each frequency. The value of dB on? determines the unit of measurement for this parameter.

  • ierrcodeclst.png 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.