Conventional f-x empirical mode decomposition（EMD） is an effective random noise attenuation method for use with seismic profiles mainly containing horizontal events.However,when a seismic event is not horizontal,the...Conventional f-x empirical mode decomposition（EMD） is an effective random noise attenuation method for use with seismic profiles mainly containing horizontal events.However,when a seismic event is not horizontal,the use of f-x EMD is harmful to most useful signals.Based on the framework of f-x EMD,this study proposes an improved denoising approach that retrieves lost useful signals by detecting effective signal points in a noise section using local similarity and then designing a weighting operator for retrieving signals.Compared with conventional f-x EMD,f-x predictive filtering,and f-x empirical mode decomposition predictive filtering,the new approach can preserve more useful signals and obtain a relatively cleaner denoised image.Synthetic and field data examples are shown as test performances of the proposed approach,thereby verifying the effectiveness of this method.展开更多
A necessary and sufficient condition for the existence of simultaneous (M,N)singular value decomposition of matrices is given.Some properties about the weighted partial ordering are discussed with the help of the deco...A necessary and sufficient condition for the existence of simultaneous (M,N)singular value decomposition of matrices is given.Some properties about the weighted partial ordering are discussed with the help of the decomposition.展开更多
文摘The paper is given the interpolation of operators between weighted Hardy spaces and weighted L p spaces when w∈A 1 by Calderon Zygmund decomposition.
基金supported by the National Natural Science Foundation of China(No.41274137)the National Engineering Laboratory of Offshore Oil Exploration
文摘Conventional f-x empirical mode decomposition（EMD） is an effective random noise attenuation method for use with seismic profiles mainly containing horizontal events.However,when a seismic event is not horizontal,the use of f-x EMD is harmful to most useful signals.Based on the framework of f-x EMD,this study proposes an improved denoising approach that retrieves lost useful signals by detecting effective signal points in a noise section using local similarity and then designing a weighting operator for retrieving signals.Compared with conventional f-x EMD,f-x predictive filtering,and f-x empirical mode decomposition predictive filtering,the new approach can preserve more useful signals and obtain a relatively cleaner denoised image.Synthetic and field data examples are shown as test performances of the proposed approach,thereby verifying the effectiveness of this method.
基金The Guangxi Science Foundation(0575032,06400161)the support program for 100 Young and Middle-aged Disciplinary Leaders in Guangxi Higher Education Institutions
文摘A necessary and sufficient condition for the existence of simultaneous (M,N)singular value decomposition of matrices is given.Some properties about the weighted partial ordering are discussed with the help of the decomposition.
