ICA在地震信号处理中的应用研究
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摘要
为了拓展独立分量分析的应用领域以及寻找地震信号去噪新方法,提出应用ICA处理地震信号随机噪声的具体方案,分析ICA的四个假设前提条件,结合实际地震信号的统计特性,分析作为源信号的有效波与噪声,并对其进行处理,使其能够在独立性和非高斯性方面满足独立分量分析算法的要求。对于盲源分离的两个固有不确定性问题,引入波形相似度的概念,使问题得到解决。从而说明在地震信号处理领域应用独立分量分析算法的可行性。最后提出算法,并用其处理合成地震信号(含随机噪声Ricker子波),实现有效波和噪声的分离,证明算法的有效性。
With the aim of using ICA in the de-noising of seismic signal,analysis the four assumption conditions of the ICA,consider with the statistical characteristics of practical seismic signal,analysis and process the source signals,make them full fill with the requirement of the requiring of ICA in independence and non gaussian are presented. The concept of waveform similarity introduce to deal with the two inherent uncertainties of Blind Source Separation. And then the feasible of using independent component analysis is proved in the application of seismic signal processing.A algorithm and then use it in the synthetic seismic signal (Ricker wavelet with Random-noise) processing are taken. Complete with the separation of wave and noise,the validity of the algorithm is proved.
With the aim of using ICA in the de-noising of seismic signal,analysis the four assumption conditions of the ICA,consider with the statistical characteristics of practical seismic signal,analysis and process the source signals,make them full fill with the requirement of the requiring of ICA in independence and non gaussian are presented. The concept of waveform similarity introduce to deal with the two inherent uncertainties of Blind Source Separation. And then the feasible of using independent component analysis is proved in the application of seismic signal processing.A algorithm and then use it in the synthetic seismic signal (Ricker wavelet with Random-noise) processing are taken. Complete with the separation of wave and noise,the validity of the algorithm is proved.
引文
1苑益军,牛滨华,王焕弟,等.去噪技术在地震资料处理中的应用.东华理工学院学报,2005;28(1):12—16
2陈遵德,段天友,朱广生,等.SVD滤波方法的改进及应用.石油地球物理勘探,1992;29(6):783—792
3Roberts S,Everson R.Independent component analysis:principle and practice.Cambridge University Press,2001
4刘喜武,刘洪,郑天愉.用独立分量分析方法实现地震转换波与多次反射波分离.防灾减灾工程学报,2003;23(1):11—19
5Hyvarinen A,Oja E.Independent component analysis:algorithms and applications.Neural Network,2000;13(4):411—430
6Satorius E H,Mulligan J J.Minimum entropy deconvolution and blind equalization.Electron Lett,1992;28(16):1534—1535
7Mendel J M.Tutorial on higher order statistics in signal processing and system theory:theoretical results and some applications.Proc IEEE,1991;79(3):278—305
2陈遵德,段天友,朱广生,等.SVD滤波方法的改进及应用.石油地球物理勘探,1992;29(6):783—792
3Roberts S,Everson R.Independent component analysis:principle and practice.Cambridge University Press,2001
4刘喜武,刘洪,郑天愉.用独立分量分析方法实现地震转换波与多次反射波分离.防灾减灾工程学报,2003;23(1):11—19
5Hyvarinen A,Oja E.Independent component analysis:algorithms and applications.Neural Network,2000;13(4):411—430
6Satorius E H,Mulligan J J.Minimum entropy deconvolution and blind equalization.Electron Lett,1992;28(16):1534—1535
7Mendel J M.Tutorial on higher order statistics in signal processing and system theory:theoretical results and some applications.Proc IEEE,1991;79(3):278—305
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