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A Syntactic Approach to Seismic Pattern Recognition

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2 Author(s)
Liu, Hsi-Ho ; School of Electrical Engineering, Purdue University, West Lafayette, IN 47907. ; Fu, K.S.

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.

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:PAMI-4 ,  Issue: 2 )