%0 Journal Article
%T Orthogonal decomposition approach of seismic data and its application
地震数据正交投影分解方法的研究与应用
%A LIU Bao-tong
%A ZHU Guang-ming
%A
刘保童
%A 朱光明
%J 地球物理学进展
%D 2005
%I
%X Orthogonal decomposition of seismic data is an important subject worth studying. The paper introduce Neural network learning algorithm to seismic data processing,propose orthogonal decomposition approach of seismic data via Neural network. In decomposed eigen subspace,by means of eigen extraction,noise is eliminated and signal to noise(s/n) ratio enhanced.The research shows,the approach is effective,because of eigen filtering only require a few primary components,a lots of computation can be avoided,so the approach can reduce computation cost,the more traces,the more effective.Finally,a real example of eigen filtering application is presented.
%K Neural networks
%K orthogonal decomposition
%K coherent noise
%K signal to noise ratio
%K wavefield separation
神经网络
%K 正交分解
%K 相干噪声
%K 信噪比
%K 波场分离
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=1E44AE713D8A6DE0&jid=65CE641AB2DEAAF8B2D39ECB6B6B6C80&aid=23AFAE9B5AD8D082&yid=2DD7160C83D0ACED&vid=A04140E723CB732E&iid=38B194292C032A66&sid=BBA8B1249CDAA6CE&eid=36C49E1242CC2C7A&journal_id=1004-2903&journal_name=地球物理学进展&referenced_num=0&reference_num=28