In the present work, the different sample collection, pretreatment and analytical methods for polycyclic aromatic hydrocarbons （PAHs） in airborne particulates is systematacially reviewed, and the applications of the...In the present work, the different sample collection, pretreatment and analytical methods for polycyclic aromatic hydrocarbons （PAHs） in airborne particulates is systematacially reviewed, and the applications of these pretreatment and analytical methods for PAHs are compared in detail. Some comments on the future expectation are also presented.展开更多
The traditional compressed sensing method for improving resolution is realized in the frequency domain.This method is aff ected by noise,which limits the signal-to-noise ratio and resolution,resulting in poor inversio...The traditional compressed sensing method for improving resolution is realized in the frequency domain.This method is aff ected by noise,which limits the signal-to-noise ratio and resolution,resulting in poor inversion.To solve this problem,we improved the objective function that extends the frequency domain to the Gaussian frequency domain having denoising and smoothing characteristics.Moreover,the reconstruction of the sparse refl ection coeffi cient is implemented by the mixed L1_L2 norm algorithm,which converts the L0 norm problem into an L1 norm problem.Additionally,a fast threshold iterative algorithm is introduced to speed up convergence and the conjugate gradient algorithm is used to achieve debiasing for eliminating the threshold constraint and amplitude error.The model test indicates that the proposed method is superior to the conventional OMP and BPDN methods.It not only has better denoising and smoothing eff ects but also improves the recognition accuracy of thin interbeds.The actual data application also shows that the new method can eff ectively expand the seismic frequency band and improve seismic data resolution,so the method is conducive to the identifi cation of thin interbeds for beach-bar sand reservoirs.展开更多
基金Projects(52071339, 51671218) supported by the National Natural Science Foundation of ChinaProject(2020JJ4739) supported by the Natural Science Foundation of Hunan Province,ChinaProject(201009-K) supported by the Guangxi Key Laboratory of Information Materials (Guilin University of Electronic Technology),China。
基金Project(52071339)supported by the National Natural Science Foundation of ChinaProject(2020JJ4739)supported by the Natural Science Foundation of Hunan Province,ChinaProject(201009-K)supported by the Guangxi Key Laboratory of Information Materials(Guilin University of Electronic Technology),China。
基金Project supported by the National Natural Science Foundation of China (No. 20437020 20575073) NSFC-JSPS Joint Research Project (No. 20511140134) the Major Research Program of Chinese Academy of Sciences (KZCX3-SW-432)
文摘In the present work, the different sample collection, pretreatment and analytical methods for polycyclic aromatic hydrocarbons （PAHs） in airborne particulates is systematacially reviewed, and the applications of these pretreatment and analytical methods for PAHs are compared in detail. Some comments on the future expectation are also presented.
基金National Science and Technology Major Project(No.2016ZX05006-002 and 2017ZX05072-001).
文摘The traditional compressed sensing method for improving resolution is realized in the frequency domain.This method is aff ected by noise,which limits the signal-to-noise ratio and resolution,resulting in poor inversion.To solve this problem,we improved the objective function that extends the frequency domain to the Gaussian frequency domain having denoising and smoothing characteristics.Moreover,the reconstruction of the sparse refl ection coeffi cient is implemented by the mixed L1_L2 norm algorithm,which converts the L0 norm problem into an L1 norm problem.Additionally,a fast threshold iterative algorithm is introduced to speed up convergence and the conjugate gradient algorithm is used to achieve debiasing for eliminating the threshold constraint and amplitude error.The model test indicates that the proposed method is superior to the conventional OMP and BPDN methods.It not only has better denoising and smoothing eff ects but also improves the recognition accuracy of thin interbeds.The actual data application also shows that the new method can eff ectively expand the seismic frequency band and improve seismic data resolution,so the method is conducive to the identifi cation of thin interbeds for beach-bar sand reservoirs.
