Minimum Cross-Entropy Spectral Analysis.

Abstract

The principle of minimum cross-entropy (minimum directed divergence) is summarized, discussed, and applied to the classical problem of estimating power spectra given samples of the autocorrelation function. This new approach reduces to maximum entropy spectral analysis (MESA) in certain special cases, and thereby provides a fundamental derivation of MESA. In contrast to MESA, the minimum cross-entropy approach makes use of prior information about the power spectrum. Depending on the extent of prior information, various alternative minimum cross-entropy spectral estimates are obtained. When a prior estimate of the power spectrum is available, the minimum cross-entropy result differs from the MESA result. Results are derived in two equivalent ways; once by minimizing the cross-entropy of underlying probability densities, and once by arguments concerning the cross-entropy between the input and output of linear filters.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 16, 1979
Accession Number
ADA064183

Entities

People

  • John E. Shore

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Autocorrelation
  • Coordinate Systems
  • Equations
  • Frequency
  • Frequency Domain
  • Information Theory
  • Military Research
  • Noise
  • Power Spectra
  • Probability
  • Random Variables
  • Signal Processing
  • Spectra
  • Stationary Processes
  • Stochastic Processes
  • White Noise

Readers

  • Image Processing and Computer Vision.
  • Statistical inference.