Correlation and Spectral Analysis VIs
- Updated2023-02-21
- 4 minute(s) read
Owning Palette: Time Series Analysis VIs
Requires: Advanced Signal Processing Toolkit. This topic might not match its corresponding palette in LabVIEW depending on your operating system, licensed product(s), and target.
Use the Correlation and Spectral Analysis VIs to perform time-domain and frequency-domain analyses on a univariate or multivariate (vector) time series. You can compute the auto-correlation and cross-correlation values, single-sided power spectral density (PSD), bispectrum, real cepstrum, and complex cepstrum with different methods.
The VIs on this palette can return general LabVIEW error codes or specific Time Series Analysis error codes.
| Palette Object | Description |
|---|---|
| Time Series Bispectrum | Computes the single-sided bispectrum of a univariate time series. |
| Time Series Cepstrum | Computes the single-sided real cepstrum of a univariate time series. |
| Time Series Spectrum | Computes the single-sided power spectral density (PSD) of a univariate time series with the periodogram, Welch, autoregressive (AR) modeling, autoregressive-moving average (ARMA) modeling, or multiple signal classification (MUSIC) method. |
| TSA AR Spectrum | 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. |
| TSA ARMA Spectrum | Computes the single-sided power spectral density (PSD) of a univariate time series based on autoregressive-moving average (ARMA) modeling. The PSD computed by this VI is exempt from window effects and has a better frequency resolution than the result from using the TSA Periodogram VI. This VI also matches the valleys in the spectrum better than the TSA AR Spectrum VI. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance. |
| TSA Auto-Correlation Function | Computes the normal or partial auto-correlation value of a univariate time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance. |
| TSA Bicoherence | Computes the bicoherence of a univariate time series. The bicoherence is the normalized value of the bispectrum. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance. |
| TSA Bispectrum | Computes the single-sided bispectrum of a univariate time series using the fast Fourier transform (FFT) or the autoregressive (AR) model based method. The bispectrum is a type of third-order spectrum, which is related to the third moment (skewness) of a time series. The resulting bispectrum can detect the asymmetric nonlinearities in the input time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance. |
| TSA Capon Spectrum | Computes the single-sided power spectral density (PSD) of a univariate time series Xt by using the Capon method. The Capon method uses a nonparametric method based on finite impulse response (FIR) filters to estimate the signal spectrum. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance. |
| TSA Complex Cepstrum | Computes the single-sided complex cepstrum of a univariate time series. This VI keeps the phase information of the input time series. You can reconstruct the original time series with the computed phase information and complex cepstrum. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance. |
| TSA Cross-Correlation Function | Computes the cross-correlation values of two univariate time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance. |
| TSA Inverse Complex Cepstrum | Reconstructs a univariate time series by inverting the complex cepstrum. Wire data to the Xt output to determine the polymorphic instance to use or manually select the instance. |
| TSA MUSIC | Computes the single-sided power spectral density (PSD) of a univariate or multivariate (vector) time series using the multiple signal classification (MUSIC) method. The MUSIC method performs a comprehensive and accurate spectral analysis on multivariate time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance. |
| TSA Periodogram | Computes the single-sided power spectral density (PSD) of a univariate time series using the periodogram method. The periodogram method is a fast Fourier transform (FFT) based method that estimates the PSD. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance. |
| TSA Real Cepstrum | 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. |
| TSA Time-Cepstrum | Computes the single-sided time-cepstrum of a univariate time series by using a sliding window. You can use the resulting time-cepstrum to detect time-varying periodic components of a time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance. |
| TSA Welch | Computes the single-sided power spectral density (PSD) of a univariate time series using the Welch method, which is a variation of the periodogram method. This VI estimates the PSD by averaging periodograms of overlapping, windowed subsequences of the time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance. |
| Subpalette | Description |
|---|---|
| Advanced PSD VIs | Use the Advanced PSD VIs to perform advanced analysis methods on the estimated power spectral density (PSD), such as averaging and liftering. The word lifter is an anagram of the word filter. |