.png){kind=icon}
返回
An Automatic P-Phase Picking Algorithm Based on Adaptive Multiband Processing
.png){kind=icon}
PRE
AI
DOI：10.1109/LGRS.2013.2260720.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This letter presents a novel picking algorithm which allows an automated determination of the P-phase onset time. The algorithm includes an adaptive multiband processing and noise-reduction techniques to allow a confident onset time estimation in signals strongly affected by background and/or nonstationary noise processes. Results using a set of 3780 computer-generated earthquake-like signals show that the accuracy is much better than that achieved by conventional STA/LTA algorithm. In addition, the accuracy of the proposed method is improved when it is combined with an autoregressive method. An application of the algorithm to a set of 400 natural earthquakes confirms that the combination of both algorithms provides a precise P-phase onset time estimation in real environments, overcoming the limitations associated with the autoregressive method.
Keyword:
Adaptive analysis
autoregressive method
enhancement filter
noise reduction
picking
P-phase arrival
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
16.4
论文数:
1.0W
被引数:
5.1K
机构
引用论文
.png){kind=icon}
Application of Richardson extrapolation to the numerical solution of partial differential equations
PREAI
分享收藏Real-world treatment patterns, healthcare resource use and clinical outcomes of patients receiving second line therapy for advanced or metastatic gastric cancer真实世界中接受二线治疗用于晚期或转移性胃癌患者的治疗模式、医疗资源使用和临床结局
OAAI
OAAI分享收藏 没有更多内容
没有更多内容