Bispectrum

In mathematics, in the area of statistical analysis, the bispectrum is a statistic used to search for nonlinear interactions.

Definitions

The Fourier transform of the second-order cumulant, i.e., the autocorrelation function, is the traditional power spectrum.

The Fourier transform of C3(t1, t2) (third-order cumulant-generating function) is called the bispectrum or bispectral density.

Calculation

Applying the convolution theorem allows fast calculation of the bispectrum :, where denotes the Fourier transform of the signal, and its conjugate.

Generalizations

Bispectra fall in the category of higher-order spectra, or polyspectra and provide supplementary information to the power spectrum. The third order polyspectrum (bispectrum) is the easiest to compute, and hence the most popular.

A statistic defined analogously is the bispectral coherency or bicoherence.

Applications

Further information: Bispectral analysis

Bispectrum and bicoherence may be applied to the case of non-linear interactions of a continuous spectrum of propagating waves in one dimension.[1]

Bispectral measurements have been carried out for EEG signals monitoring.[2] It was also shown that bispectra characterize differences between families of musical instruments.[3]

In seismology, signals rarely have adequate duration for making sensible bispectral estimates from time averages.

See also

References

  1. Greb U, Rusbridge MG (1988). "The interpretation of the bispectrum and bicoherence for non-linear interactions of continuous spectra". Plasma Phys. Control. Fusion. 30 (5): 537–49. doi:10.1088/0741-3335/30/5/005.
  2. Johansen JW, Sebel PS (November 2000). "Development and clinical application of electroencephalographic bispectrum monitoring". Anesthesiology. 93 (5): 1336–44. doi:10.1097/00000542-200011000-00029. PMID 11046224.
  3. Dubnov S, Tishby N and Cohen D. (1997). "Polyspectra as Measures of Sound Texture and Timbre". Journal of New Music Research. 26: 277–314. doi:10.1080/09298219708570732.
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