These codes generally import the preprocessed seismic data to calculate RFs from teleseismic radial and vertical components. Many open-source codes have been released for RF analysis in recent years, such as the CPS 330 system, the RF module under Python, and the process RFmatlab module under MATLAB. Zhu and Kanamori ( 2000) further proposed the H- k stacking method with a grid-search algorithm that determines the v P/ v S ratio and Moho depth ( H) with the obtained P-wave RFs at a station, which is very important in determining one-dimensional structure in the Earth. The routines of RF analysis include the following procedures: (a) selecting the proper events (e.g., epicentral distance, magnitude) from the earthquake catalog and matching them with seismic data in the local directory (b) preprocessing the waveforms, such as removing average shift of amplitude, removing the linear trend, and filtering the waveforms with certain bandpass filters (c) picking P-wave arrivals and (d) calculating P-wave RFs by deconvolving the radial component with the vertical component. 2002), which makes it one of the most popular methods in seismology. The RF method is stable and efficient in determining the crustal and upper mantle structures (e.g., Dueker and Sheehan 1997 Kind et al. The time delay between the Ps converted phase and direct P-wave is sensitive to the depth of the velocity discontinuities and the average S-wave velocity above it (Zhu and Kanamori 2000). P-wave RF deconvolves the radial component with the vertical component and obtains the Ps phase converted at velocity discontinuities (e.g., Moho) in the Earth.

Receiver function (RF) analysis, proposed by Langston ( 1979), is one of routine tools to determine the one-dimensional structure of the crust and mantle. Seismology is becoming the most popular tool in studying the interior structure of the Earth thanks to the development of digital seismology and the rapidly accumulated seismic data in recent years.

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