On Modeling the Distribution of Non-Gaussian Ambient Noise.

Abstract

The applicability of tractable first-order non-Gaussian models for the ambient noise probability distribution is investigated. The models considered here are the Gauss-Gauss mixture model and the Johnson S system of probability density functions. The moment generating function method is used to fit the sample data to the Gauss-Gauss mixture model while the method of quantile matching is used to fit the data to the Johnson probability density functions. The results show that the Johnson system may be computationally more tractable in its application and more robust to nonstationary behavior in the data.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1987
Accession Number
ADA191910

Entities

People

  • William C. Torrez

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Ambient Noise
  • Classification
  • Computer Science
  • Computers
  • Data Science
  • Information Science
  • Monitoring
  • Noise
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Security
  • Statistics
  • Theoretical Computer Science

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  • Regression Analysis.