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Bispectrum Estimation Using Overlapped Segments

  • J. Piñeyro
  • K. Behringer

Abstract

The power spectral density (PSD) function cannot detect nonlinear random processes which effect non-Gaussian contributions to the noise signal. For the characterization of non-Gaussian noise contributions, higher-order cumulant functions or their corresponding Fourier transforms must be considered (e.g. Hasselmann et al., 1963; Brillinger, 1965; Bendat and Piersol, 1982). The triple correlation function or the bispectrum, respectively, are the next higher approaches, provided that a skewness exists. There are also interesting applications to deterministic signals, which are often obscured by background noise (Sato and Sasaki, 1977; Lohmann and Wirnitzer, 1984).

Keywords

Power Spectral Density Side Lobe Side Lobe Level Signal Window Power Spectral Density Estimation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Plenum Press, New York 1989

Authors and Affiliations

  • J. Piñeyro
    • 1
  • K. Behringer
    • 1
  1. 1.Paul Scherrer InstituteWürenlingenSwitzerland

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