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dc.contributor.authorHuang, Kou-Yuanen_US
dc.contributor.authorHsieh, Wen-Hsuanen_US
dc.date.accessioned2018-08-21T05:57:06Z-
dc.date.available2018-08-21T05:57:06Z-
dc.date.issued2017-01-01en_US
dc.identifier.issn2153-6996en_US
dc.identifier.urihttp://hdl.handle.net/11536/147061-
dc.description.abstractCellular neural network is adopted for seismic pattern recognition. We design cellular neural network to behave as associative memory according to the stored patterns, and finish the training process of the network. Then we use this associative memory to recognize seismic test patterns. In the experiments, the analyzed seismic patterns are bright spot pattern, right and left pinch-out patterns. From the recognition results, the noisy seismic patterns can be recovered. Seismic pattern recognition can help the analysis and interpretation of seismic data.en_US
dc.language.isoen_USen_US
dc.subjectCellular neural networken_US
dc.subjectpattern recognitionen_US
dc.subjectseismic patternsen_US
dc.titleSeismic Pattern Recognition Using Cellular Neural Networken_US
dc.typeProceedings Paperen_US
dc.identifier.journal2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)en_US
dc.citation.spage3712en_US
dc.citation.epage3715en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000426954603200en_US
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