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Time-Dependent Spectra for Non-Stationary Stochastic Processes

  • P. Flandrin
Part of the International Centre for Mechanical Sciences book series (CISM, volume 309)

Abstract

An overview of non-parametric approaches to time-dependent spectral analysis of non-stationary stochastic processes is provided. Possible definitions, which are based either on the spectral representation of the processes or on their covariance function, are derived from a priori requirements. Their respective merits, concerning both theoretical and practical properties, are evaluated and compared by means of typical examples. Estimation procedures are addressed and the usefulness of timefrequency descriptions for gaining new insights in some statistical Signal Processing problems is discussed.

Keywords

Power Spectral Density Covariance Function Fractional Brownian Motion Wigner Distribution Dependent Spectrum 
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

© Springer-Verlag Wien 1989

Authors and Affiliations

  • P. Flandrin
    • 1
  1. 1.Laboratoire de Treitement du SignalLyonFrance

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