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An application of syntactic pattern recognition to seismic discrimination

Journal Article · · IEEE Trans. Geosci. Remote Sens.; (United States)
Two syntactic methods for the recognition of seismic waveforms are presented in this paper. The seismic waveforms are represented by strings of primitives. Primitive extraction is based on 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 data for earthquake/ explosion is presented as an application example.
Research Organization:
Dept. of Elec. and Computer Eng., Univ. of Miami, Coral Gables, FL 33124
OSTI ID:
5475221
Journal Information:
IEEE Trans. Geosci. Remote Sens.; (United States), Journal Name: IEEE Trans. Geosci. Remote Sens.; (United States) Vol. GE-21:2; ISSN IGRSD
Country of Publication:
United States
Language:
English

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