完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Huang, Kou-Yuan | en_US |
dc.contributor.author | Hsieh, Wen-Hsuan | en_US |
dc.date.accessioned | 2018-08-21T05:57:06Z | - |
dc.date.available | 2018-08-21T05:57:06Z | - |
dc.date.issued | 2017-01-01 | en_US |
dc.identifier.issn | 2153-6996 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/147061 | - |
dc.description.abstract | Cellular 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.iso | en_US | en_US |
dc.subject | Cellular neural network | en_US |
dc.subject | pattern recognition | en_US |
dc.subject | seismic patterns | en_US |
dc.title | Seismic Pattern Recognition Using Cellular Neural Network | en_US |
dc.type | Proceedings Paper | en_US |
dc.identifier.journal | 2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | en_US |
dc.citation.spage | 3712 | en_US |
dc.citation.epage | 3715 | en_US |
dc.contributor.department | 資訊工程學系 | zh_TW |
dc.contributor.department | Department of Computer Science | en_US |
dc.identifier.wosnumber | WOS:000426954603200 | en_US |
顯示於類別: | 會議論文 |