On Higher-Order Spectral Moments and the Normality of Random Processes: Application to Linear and Nonlinear Transformations,

Abstract

The authors apply the theory of higher-order spectral moments to the problem of narrow-band filtering of random processes. The authors prove that the output converges to a Gaussian process. The authors pay particular attention to the rate of convergence and to methods to increase this rate. It is shown that band-pass filters are better behaved in this respect than low-pass filters of equal bandwidth. For a large class of processes it is shown that memoryless nonlinear transformations spread the output spectrum. In particular, this is true for Gaussian processes.

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1973
Accession Number
ADA003732

Entities

People

  • A. Traganitis
  • J. B. Thomas

Organizations

  • Princeton University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Bandwidth
  • Convergence
  • Data Science
  • Filters
  • Filtration
  • Gaussian Processes
  • Information Science
  • Low Pass Filters
  • Normality
  • Spectra

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Radio communications and signal processing.
  • Regression Analysis.