Title :
A Syntactic Approach to Seismic Pattern Recognition
Author :
Liu, Hsi-Ho ; Fu, K.S.
Author_Institution :
School of Electrical Engineering, Purdue University, West Lafayette, IN 47907.
fDate :
3/1/1982 12:00:00 AM
Abstract :
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.
Keywords :
Earthquakes; Explosions; Information analysis; Noise shaping; Pattern analysis; Pattern classification; Pattern recognition; Seismic measurements; Seismic waves; Testing; Error-correcting parsing; grammatical inference; nearest-neighbor rule; seismic discrimination; string distance; syntactic pattern recognition;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1982.4767219