BSS algorithm based on ICA and its application in seismic signal noise elimination

摘要：

Many random interference signals exist in seismic prospecting,which deeply influence the quality of seismic profile,and dont benefit to make correct geological interpretation,so denoising should be done.Independent Component Analysis(ICA) is a signal processing method which is developing with the problem of Blind Source Separation(BSS),and it has broad application values in modem engineering field.The paper introduces the BSS problem and ICA arithmetic model,gives a Fast ICA algorithm based on maximum negentropy,discusses its application in seismic signal noise elimination.Finally a simulation experiment verifies the effectiveness of ICA algorithm.

关键词： independent component analysis blind source separation seismic signal noise elimination

作者: Nian Zhang Tianyou Liu Ming Wang

作者单位: Institute of Geophysics and Geomatics,China University of Geosciences,Wuhan 430074,China Department Institute of Geophysics and Geomatics,China University of Geosciences,Wuhan 430074,China Institute of Geophysics and Information Technology,China University of Geosciences,Beijing 100083,Ch

会议类型: 国际会议

会议名称: The 3rd International Conference on Environmental and Engineering Geophysics(第三届环境与工程地球物理国际会议)

会议地点: 武汉

会议语种:英文

页码: 219-222

在线出版日期: 2008-06-15（万方平台首次上网日期，不代表论文的发表时间）