An Application of Syntactic Pattern Recognition to Seismic Discrimination,

Abstract

Two syntactic methods for the recognition of seismic waveforms are presented in this paper. The seismic waveforms are represented by sentences (strings of primitives). Primitive extraction is based on a cluster analysis. Finite-state grammars are inferred from the training samples. The nearest-neighbor decision rule and error-correcting finite-state parsers are used for pattern classification. While both show equal recognition performance, the nearest-neighbor rule is much faster in computation speed. The classification of real earthquake/explosion data is presented as an application example. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1981
Accession Number
ADA107383

Entities

People

  • Hsi Ho Liu
  • King Sun Fu

Organizations

  • Purdue University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Computations
  • Computer Programming
  • Computers
  • Electrical Engineering
  • Engineering
  • Explosions
  • Feature Selection
  • Grammars
  • Language
  • New York
  • Pattern Recognition
  • Recognition
  • Seismic Discrimination
  • Seismic Waves
  • Waves

Readers

  • Computational Linguistics
  • Computer Vision.
  • Seismology

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation