CSDL Home IEEE Transactions on Pattern Analysis & Machine Intelligence 1982 vol.4 Issue No.02 - February
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.
Hsi-Ho Liu, K. S. Fu, "A Syntactic Approach to Seismic Pattern Recognition", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.4, no. 2, pp. 136-140, February 1982, doi:10.1109/TPAMI.1982.4767219