NEURAL NETWORKS AND DISCRIMINATION OF SEISMIC SIGNALS

被引：11
|
作者：
ROMEO, G
MELE, F
MORELLI, A
机构：
[1] Istituto Nazionale di Geofisica, 00143 Roma
来源：
COMPUTERS & GEOSCIENCES | 1995年 / 21卷 / 02期
关键词：
ERROR BACKPROPAGATION; MULTILAYER PERCEPTRON; NEURAL NETWORK; PERCEPTRON; SEISMOLOGY; SEISMIC NETWORK;
D O I：
10.1016/0098-3004(94)00072-3
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Recent developments in algorithms and computer architecture make neural networks a useful tool in designing pattern recognition systems. We show how a simple multilayer perceptron with 23 neurons can be trained easily and used to classify seismic signals. Applied to broadband seismic signal, the perceptron permitted the recognition of different types of events on the basis of their frequency. Applied to a real-time, automatic, seismic data acquisition system, it saved more than 50% CPU time in a detection procedure.
引用
收藏
页码：279 / 288
页数：10
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