A neural network based identification system for VIRGO seismic noise

被引：0
|
作者：
Acernese, F [1 ]
Barone, F [1 ]
De Rosa, R [1 ]
Eleuteri, A [1 ]
Milano, L [1 ]
Tagliaferri, R [1 ]
机构：
[1] Univ Naples, Dipartimento Sci Fis, I-80126 Naples, Italy
来源：
IJCNN'01: INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, PROCEEDINGS | 2001年
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：
In this paper a Neural Network-based approach is presented for the real time seismic noise identification of GW laser interferometric antenna. The procedure allows the estimation of seismic events in a background noise. The recognition of such events is very important for the data quality of the interferometer output. The algorithm we propose is quite general and robust, taking into account that it does not requires a-priori informations on the data, nor precise model, and constitute a powerful tool for quality data analysis.
引用
收藏
页码：252 / 257
页数：6
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