Artificial Intelligence Applied to Spectrum Estimation.

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. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1984
Accession Number
ADA142202

Entities

People

  • J. E. Gaby
  • M. H. Hayes

Organizations

  • Georgia Tech

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Intelligence
  • Case Studies
  • Composite Materials
  • Electrical Engineering
  • Engineering
  • Expert Systems
  • High Resolution
  • Models
  • Power Spectra
  • Recognition
  • Signal Generation
  • Signal Processing
  • Spectra
  • Stationary
  • Wave Propagation
  • Waveforms

Fields of Study

  • Engineering

Readers

  • Artificial Intelligence
  • Spectroscopy.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - DoD AI Strategy