• DocumentCode
    388532
  • Title

    Artificial intelligence applied to spectrum estimation

  • Author

    Gaby, James H. ; Hayes, Monson H.

  • Author_Institution
    Georgia Institute of Technology, Atlanta, Georgia
  • Volume
    9
  • fYear
    1984
  • fDate
    30742
  • Firstpage
    546
  • Lastpage
    549
  • Abstract
    Many techniques are available for the estimation of the power spectrum of a stationary random process. While power spectrum estimation is a problem which falls within the domain of signal processing, the problem of inferring information falls within the domain of artificial intelligence (AI). With a wide variety of different types of power spectrum estimation techniques to choose from, an equally wide range of differing spectral estimates may be produced. Each estimate, however, may be used to infer information about the time series. By defining an appropriate knowledge base, a system is being developed to infer information from power spectrum estimates. This system combines the estimates produced by a variety of current spectrum estimation techniques in order to formulate a composite spectral estimate.
  • Keywords
    Artificial intelligence; Corporate acquisitions; Data mining; Power engineering and energy; Prototypes; Random processes; Signal generators; Signal processing; Spectral analysis; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '84.
  • Type

    conf

  • DOI
    10.1109/ICASSP.1984.1172313
  • Filename
    1172313