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Seismic time frequency spectrum analysis based on local polynomial Fourier transform

机译:基于局部多项式傅里叶变换的地震时间频谱分析

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Time frequency analysis technology is widely used in non-stationary seismic data analysis. The energy concentration of the spectrum depends on the consistency of the kernel function of the time frequency analysis method and the instantaneous frequency variation of the signals. The conventional time frequency analysis methods usually require that the local instantaneous frequency of the signals remains unchanged or linearly changed. So it is difficult to accurately characterize the instantaneous frequency nonlinear variation of the non-stationary signal. The local polynomial Fourier transform (LPFT) method can effectively describe the instantaneous frequency variation by local high-order polynomial fitting and obtain the results with high spectral and energy concentration. The numerical simulations and field seismic data applications show that the time frequency spectrum results obtained by LPFT can reflect the instantaneous frequency variation characteristics of the seismic data, while ensuring the concentration of time frequency energy.
机译:时间频率分析技术广泛用于非静止地震数据分析。光谱的能量浓度取决于时频分析方法的核功能的一致性和信号的瞬时频率变化。传统的时间频率分析方法通常要求信号的局部瞬时频率保持不变或线性改变。因此,难以准确地表征非静止信号的瞬时频率非线性变化。本地多项式傅里叶变换(LPFT)方法可以有效地描述本地高阶多项式拟合的瞬时频率变化,并通过高光谱和能量浓度获得结果。数值模拟和场地震数据应用表明,LPFT获得的时间频谱结果可以反映地震数据的瞬时频率变化特性,同时确保时间频率能量的浓度。

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