An Application of Signal Analysis and Pattern Recognition to Study a Simple Ground Motion Problem.

Abstract

A simple problem involving the identification of an explosive source as being unbermed or bermed using a pattern recognition based analysis of buried ground accelerometer measurements is presented. This problem illustrates the advantages of computerized information extraction from the measured waveforms. Information was extracted from the frequency and cepstrum descriptions of the waveforms in addition to the more traditional time domain information. These signal features were incorporated into a Fisher's Linear Discriminant pattern recognition procedure. Previously unseen signals were classified with up to 100% accuracy depending on which features were used. Close in explosive source measurements present unique problems to a pattern recognition based analysis approach. These problems are reviewed and approaches illustrated.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1986
Accession Number
ADA174463

Entities

People

  • James M. Carson

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Civil Engineering
  • Data Sets
  • Databases
  • Explosives
  • Feature Extraction
  • Feature Selection
  • Frequency Domain
  • Identification
  • Information Processing
  • Information Science
  • Measurement
  • Pattern Recognition
  • Probability
  • Probability Density Functions
  • Recognition
  • Signal Processing
  • Two Dimensional

Readers

  • Neural Network Machine Learning.
  • Seismology
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms