Hough transform neural network for seismic pattern detection

Kou-Yuan Huang*, Jiun De You, Kai Ju Chen, Hung Lin Lai, An Jin Don

*Corresponding author for this work

研究成果: Conference contribution同行評審

摘要

Hough transform neural network is adopted to detect line pattern of direct wave and hyperbola pattern of reflection wave in a seismogram. The distance calculation from point to hyperbola is calculated from the time difference. This calculation makes the parameter learning feasible, The neural network can calculate the total error for distance from point to patterns. The parameter learning rule is derived by gradient descent method to minimize the total error. Experimental results show that line and hyperbola can be detected in both simulated and real seismic data. The network can get a fast convergence. The detection results can improve the seismic interpretation.

原文English
主出版物標題Neural Information Processing - 13th International Conference, ICONIP 2006, Proceedings
發行者Springer Verlag
頁面60-69
頁數10
ISBN(列印)3540464816, 9783540464815
DOIs
出版狀態Published - 1 一月 2006
事件13th International Conference on Neural Information Processing, ICONIP 2006 - Hong Kong, China
持續時間: 3 十月 20066 十月 2006

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4233 LNCS - II
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference13th International Conference on Neural Information Processing, ICONIP 2006
國家China
城市Hong Kong
期間3/10/066/10/06

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