Investigation of Spectral-Based Techniques for Classification of Wideband Transient Signals in Additive White Gaussian Noise

Abstract

Spectral-based classification schemes designed to separate various wide band transient signals in added noise have been identified and their performances compared along with those obtained using a back-propagation neural network implementation. The spectral-based measures used include: the normalized cross-correlation coefficient; the modified normalized cross-correlation coefficient, and; the divergence and the Bhattacharyya distance. Noise was added to the signals to create signal to noise ratios of 0 dB to -20 dB. Results show that as noise levels increase, the modified normalized cross-correlation coefficient spectral measure remains the most robust scheme.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1994
Accession Number
ADA282954

Entities

People

  • David A. Derieux

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Amplitude
  • Computers
  • Correlation Techniques
  • Cross Correlation
  • Data Science
  • Data Sets
  • Engineering
  • Frequency
  • Gaussian Noise
  • Information Science
  • Neural Networks
  • Numbers
  • Power Spectra
  • Spectra
  • Square Roots
  • Time Domain

Fields of Study

  • Engineering

Readers

  • Internal Combustion Engine (ICE) Technology.
  • Radar Systems Engineering.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference