Issue No. 02 - February (1982 vol. 4)
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.
K. S. Fu and H. Liu, "A Syntactic Approach to Seismic Pattern Recognition," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 4, no. , pp. 136-140, 1982.