Hough transform neural network for seismic pattern detection

被引：0
|
作者：
Huang, Kou-Yuan [1 ]
You, Jiun-De [1 ]
Chen, Kai-Ju [1 ]
Lai, Hung-Lin [1 ]
Don, An-Jin [1 ]
机构：
[1] Natl Chiao Tung Univ, Dept Comp Sci, Hsinchu 30039, Taiwan
来源：
NEURAL INFORMATION PROCESSING, PT 2, PROCEEDINGS | 2006年 / 4233卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
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.
引用
收藏
页码：60 / 69
页数：10
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