Spectra and Covariances for 'Classical' Nonlinear Signal Processing Problems Involving Class A Non-Gaussian Noise

Abstract

Because of the critical role of non-Gaussian noise processes in modern signal processing, which usually involves nonlinear operations, it is important to examine the effects of the latter on such noise and the extension to added signal inputs. Here, only non-Gaussian (specifically CLass A) noise inputs, with an additive Gaussian component, are considered. The classical problems of zero-memory nonlinear (ZMNL) devices serve to illustrate the approach and to provide a variety of useful output statistical quantities, e.g., mean or dc values, mean intensities, covariances, and their associated spectra. Here, Gaussian and non-Gaussian noise fields are introduced, and their respective temporal and spatial outputs are described and numerically evaluated for representative parameters of the noise and the ZMNL devices.

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Document Details

Document Type
Technical Report
Publication Date
May 21, 1991
Accession Number
ADA237388

Entities

People

  • Albert H. Nuttall
  • David Middleton

Organizations

  • Naval Underwater Systems Center

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Bandwidth
  • Covariance
  • Data Science
  • Detectors
  • Diffraction
  • Frequency
  • Frequency Modulation
  • Gaussian Noise
  • Information Processing
  • Information Science
  • Intensity
  • Modulation
  • Noise
  • Phase Modulation
  • Signal Processing
  • Spectra
  • Statistics

Readers

  • Acoustics.
  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Statistical inference.