This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
A Syntactic Approach to Seismic Pattern Recognition
February 1982 (vol. 4 no. 2)
pp. 136-140
Hsi-Ho Liu, School of Electrical Engineering, Purdue University, West Lafayette, IN 47907.
K. S. Fu, School of Electrical Engineering, Purdue University, West Lafayette, IN 47907.
The nearest-neighbor decision rule for syntactic patterns is applied to seismic pattern classification. Each pattern is represented by a string. The string-to-string distance is used as a similarity measure. Another method using finite-state grammars inferred from the training samples and error-correcting parsers is also implemented. Both methods show equal recognition accuracy; however, the nearest-neighbor rule is much faster in computation speed. The classification results of real earthquake/explosion data are presented.
Citation:
Hsi-Ho Liu, K. S. Fu, "A Syntactic Approach to Seismic Pattern Recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 4, no. 2, pp. 136-140, Feb. 1982, doi:10.1109/TPAMI.1982.4767219
Usage of this product signifies your acceptance of the Terms of Use.