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Discrimination Information in Phase Amplitude Thresholds with Application to Western China Regional Data

机译:相振幅阈值的判别信息及其在中国西部地区数据中的应用

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摘要

This article develops a regional seismic discrimination method using information inherent in phase amplitudes that are unmeasurable due to small signal amplitudes and high noise levels. The method, quadratic negative evidence discrimination (QNED), is an enhancement to the teleseismic techniques proposed by Elvers (1974) and is extended to regional discrimination. The method presented in this article is developed for a single seismic station and makes use of the empirical evidence in the regional P_g versus L_g discriminant (see Pomeroy et al., 1983). We develop the equations necessary to compute the station-specific, missed-explosion, and false-alarm error rates. These error rates depend on the required minimum signal-to-noise ration (S/N) and can be adjusted, within limits, to desired levels. We also show that these equations are an accurate assessment of the errors in seismic discrimination. We propose that many of the current approaches to assessing seismic discrimination errors are often overly optimistic. For some applications, this disparity can be significant. For an application to Western China regional data [P_g versus L_g (1.5 to 3 hZ)], a widely used estimate of the missed-explosion error rate is 20%, leading to the perception that explosions can be identified with an accuracy rate of 80%. A proper accounting of the missed-explosion error rate, using QNED, shows that explosions can be identified with accuracy rate of only 73%.
机译:本文开发了一种区域地震判别方法,使用了由于信号振幅小和噪声水平高而无法测量的相位振幅固有的信息。二次阴性证据鉴别(QNED)方法是Elvers(1974)提出的远程地震技术的增强,并扩展到了区域鉴别。本文介绍的方法是针对单个地震台站开发的,并利用了在地区P_g与L_g判别中的经验证据(参见Pomeroy等人,1983)。我们开发了必要的方程式,以计算特定于站点的,爆炸失败和误报错误率。这些错误率取决于所需的最小信噪比(S / N),并且可以在限制范围内调整到所需的水平。我们还表明,这些方程式是对地震判别误差的准确评估。我们提出,当前评估地震判别误差的许多方法通常过于乐观。对于某些应用程序,此差异可能很大。对于中国西部地区数据的应用[P_g与L_g(1.5至3 hZ)],广泛使用的漏失错误率估计为20%,这导致人们认为可以以80的准确率识别爆炸。 %。使用QNED正确地计算了爆炸遗漏的错误率,表明可以以73%的准确率识别爆炸。

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