TSA Real Cepstrum (Waveform) VI
- Updated2024-07-30
- 4 minute(s) read
Computes the single-sided real cepstrum of a univariate time series. You can use the resulting real cepstrum to detect the periodicities of the time series. The real cepstrum does not keep the phase information of the time series, so you cannot reconstruct the original time series from the real cepstrum. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.

Inputs/Outputs
![]() cepstrum bins specifies the number of time points. This VI computes the cepstrum for each time point. The default is -1, which specifies that the number of cepstrum bins equals the length of the input time series. ![]() Xt specifies the univariate time series. ![]() method specifies whether this VI uses the FFT-based or the autoregressive (AR) model-based method to compute the real cepstrum. The default is FFT. ![]() window specifies the time-domain window applied to the time series. Options include None (default), Hanning, Hamming, Blackman-Harris, Exact Blackman, Blackman, Flat Top, 4 Term B-Harris, 7 Term B-Harris, and Low Sidelobe. ![]() error in describes error conditions that occur before this node runs. This input provides standard error in functionality. ![]() AR setting specifies the settings for the autoregressive (AR) model. This option is valid only when the method is AR Model.
![]() cepstrum returns the cepstrum information about Xt.
![]() 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 contains error information. This output provides standard error out functionality. |
TSA Real Cepstrum Details
When method is FFT, this VI computes the real cepstrum of a univariate time series according to the following equation:
Xt is the univariate time series and is the real cepstrum of Xt.
When method is AR Model, this VI computes the real cepstrum of a univariate time series according to the following equation:
s is the standard deviation of estimated noise series of AR model of Xt and a is the estimated coefficients of AR model. a = [1, a1, a2,…, ak].
Examples
Refer to the following VIs for examples of using the TSA Real Cepstrum VI:
- Bearing Monitor VI: labview\examples\Time Series Analysis\TSAApplications
- Cepstrum Analysis VI: labview\examples\Time Series Analysis\TSAGettingStarted