基于时间结构盲源分离算法的工频干扰消除
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摘要
研究了基于时间结构盲源分离算法的基本原理,在分析其特点和适用范围的基础上,提出了采用时间结构盲源分离算法消除地震信号采集过程中工频干扰的方法,并与基于FastICA的方法进行了性能比较。研究结果表明,本方法能够有效地消除地震信号中的工频干扰,同时保护有用信号,且干扰消除性能具有明显优势。
The basic principle of blind source separation algorithm based on temporal structure is investigated.Character and application area for blind source separation algorithm based on temporal structure is analyzed.Power interference removal method in seismic signal collection using temporal structure BSS algorithm is proposed and the property is compared with the method based on FastICA.The results indicate that this method can effectively eliminate power interference from seismic signal,while protecting the desired signal,and interference removal performance has an obvious advantage.
The basic principle of blind source separation algorithm based on temporal structure is investigated.Character and application area for blind source separation algorithm based on temporal structure is analyzed.Power interference removal method in seismic signal collection using temporal structure BSS algorithm is proposed and the property is compared with the method based on FastICA.The results indicate that this method can effectively eliminate power interference from seismic signal,while protecting the desired signal,and interference removal performance has an obvious advantage.
引文
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[12]刘洋.强工频干扰波的提取与消除方法[J].石油物探,2003,42(2):154-159.
[13]吴小培,詹长安,周荷琴,冯焕清.采用独立分量分析方法消除信号中的工频干扰[J].中国科技大学学报,2000,30(6):671-676.
[2]沈凤麟.生物医学随机信号处理[M].合肥:中国科技大学出版社,1999.
[3]S Haykin.Unsupervised Adaptive Filtering,Blind Source Separation[M].New York:Wiley.2000.
[4]A Hyvarinen,J Karhunen,et al.Independent Component Analysis[M].New York:Wiley.2001.
[5]A J Bell,T J Sejnowski.An information-maximization approach to blind separation and blind deconvolution[J].Neural Computation,1995,7(6):1129-1159.
[6]T W Lee,M Girolami,T J Sejnowski.Independent component analysis using an extended infomax algorithm for mixed sub-Gaussian andsuper-Gaussian sources[J].Neural Computation,1999,11(2):417-441.
[7]S Amari,A Cichocki,H H Yang.A new learning algorithm for blind signal separation[A].In:Advances in Neural Information ProcessingSystems[C].Cambridge,MA:MIT Press,1996.757-763.
[8]A Hyvarinen.Fast and robust fixed-point algorithms for independent component analysis[J].IEEE Trans on Neural Networks,1999,10(3):626-634.
[9]J V Stone.Blind source separation using temporal predictability[J].Neural Computation,2001,(13):1559-1574.
[10]杨再朝,赵建顺.用反相叠加法消除工频干扰[J].石油地球物理勘探,1986,21(4):405-409.
[11]凌云,高军,张汝杰,王丹.随时间推移地震勘探处理方法研究[J].石油地球物理勘探,2001,36(2):173-179.
[12]刘洋.强工频干扰波的提取与消除方法[J].石油物探,2003,42(2):154-159.
[13]吴小培,詹长安,周荷琴,冯焕清.采用独立分量分析方法消除信号中的工频干扰[J].中国科技大学学报,2000,30(6):671-676.
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