Irregular seismic data causes problems with multi-trace processing algorithms and degrades processing quality. We introduce the Projection onto Convex Sets （POCS） based image restoration method into the seismic data...Irregular seismic data causes problems with multi-trace processing algorithms and degrades processing quality. We introduce the Projection onto Convex Sets （POCS） based image restoration method into the seismic data reconstruction field to interpolate irregularly missing traces. For entire dead traces, we transfer the POCS iteration reconstruction process from the time to frequency domain to save computational cost because forward and reverse Fourier time transforms are not needed. In each iteration, the selection threshold parameter is important for reconstruction efficiency. In this paper, we designed two types of threshold models to reconstruct irregularly missing seismic data. The experimental results show that an exponential threshold can greatly reduce iterations and improve reconstruction efficiency compared to a linear threshold for the same reconstruction result. We also analyze the anti- noise and anti-alias ability of the POCS reconstruction method. Finally, theoretical model tests and real data examples indicate that the proposed method is efficient and applicable.展开更多
A small problem about soil particle regularization and contacts but essential to geotechnical engineering was studied.The soils sourced from Guangzhou and Xiamen were sieved into five different particle scale ranges(d...A small problem about soil particle regularization and contacts but essential to geotechnical engineering was studied.The soils sourced from Guangzhou and Xiamen were sieved into five different particle scale ranges(d<0.075 mm,0.075 mm≤d<0.1 mm,0.1 mm≤d<0.2 mm,0.2 mm≤d<0.5 mm and 0.5 mm≤d<1.0 mm)to study the structures and particle contacts of granite residual soil.The X-ray micro computed tomography method was used to reconstruct the microstructure of granite residual soil.The particle was identified and regularized using principal component analysis(PCA).The particle contacts and geometrical characteristics in 3D space were analyzed and summarized using statistical analyses.The results demonstrate that the main types of contact among the particles are face-face,face-angle,face-edge,edge-edge,edge-angle and angle-angle contacts for particle sizes less than 0.2 mm.When the particle sizes are greater than 0.2 mm,the contacts are effectively summarized as face-face,face-angle,face-edge,edge-edge,edge-angle,angle-angle,sphere-sphere,sphere-face,sphere-edge and sphere-angle contacts.The differences in porosity among the original sample,reconstructed sample and regularized sample are closely related to the water-swelling and water-disintegrable characteristics of granite residual soil.展开更多
The chaotic nonlinear time series method is applied to analyze the sliver irregularity in textile processing.Because it unifies the system's determinacy and randomness,it seems more adaptive to describe the sliver...The chaotic nonlinear time series method is applied to analyze the sliver irregularity in textile processing.Because it unifies the system's determinacy and randomness,it seems more adaptive to describe the sliver irregularity than conventional methods.Firstly,the chaos character,i.e.fractal dimension,positive Lyapunov exponent,and state space parameters,including time delay and reconstruction dimension,are calculated respectively.As a result,a positive Lyapunov exponent and a fractal dimension are obtained,which demonstrates that the system is chaotic in fact.Secondly,both local linear forecast and global forecast models based on the reconstructed state are adopted to predict a segment part of the sliver irregularity series,which proves the validity of this analysis.Therefore,the sliver irregularity series shows the evidence of chaotic phenomena,and thus laying the theoretical foundation for analyzing and modeling the sliver irregularity series by applying the chaos theory,and providing a new way to understand the complexity of the sliver irregularity much better.展开更多
In this paper, we mainly pay attention to the weighted sampling and reconstruction algorithm in lattice-invariant signal spaces. We give the reconstruction formula in lattice-invariant signal spaces, which is a genera...In this paper, we mainly pay attention to the weighted sampling and reconstruction algorithm in lattice-invariant signal spaces. We give the reconstruction formula in lattice-invariant signal spaces, which is a generalization of former results in shift-invariant signal spaces. That is, we generalize and improve Aldroubi, Groechenig and Chen＇s results, respectively. So we obtain a general reconstruction algorithm in lattice-invariant signal spaces, which the signal spaces is sufficiently large to accommodate a large number of possible models. They are maybe useful for signal processing and communication theory.展开更多
基金financially supported by National 863 Program (Grants No.2006AA 09A 102-09)National Science and Technology of Major Projects ( Grants No.2008ZX0 5025-001-001)
文摘Irregular seismic data causes problems with multi-trace processing algorithms and degrades processing quality. We introduce the Projection onto Convex Sets （POCS） based image restoration method into the seismic data reconstruction field to interpolate irregularly missing traces. For entire dead traces, we transfer the POCS iteration reconstruction process from the time to frequency domain to save computational cost because forward and reverse Fourier time transforms are not needed. In each iteration, the selection threshold parameter is important for reconstruction efficiency. In this paper, we designed two types of threshold models to reconstruct irregularly missing seismic data. The experimental results show that an exponential threshold can greatly reduce iterations and improve reconstruction efficiency compared to a linear threshold for the same reconstruction result. We also analyze the anti- noise and anti-alias ability of the POCS reconstruction method. Finally, theoretical model tests and real data examples indicate that the proposed method is efficient and applicable.
基金Projects(41572277,41877229) supported by the National Natural Science Foundation of ChinaProject(2015A030313118) supported by the Natural Science Foundation of Guangdong Province,ChinaProject(201607010023) supported by the Science and Technology Program of Guangzhou,China
文摘A small problem about soil particle regularization and contacts but essential to geotechnical engineering was studied.The soils sourced from Guangzhou and Xiamen were sieved into five different particle scale ranges(d<0.075 mm,0.075 mm≤d<0.1 mm,0.1 mm≤d<0.2 mm,0.2 mm≤d<0.5 mm and 0.5 mm≤d<1.0 mm)to study the structures and particle contacts of granite residual soil.The X-ray micro computed tomography method was used to reconstruct the microstructure of granite residual soil.The particle was identified and regularized using principal component analysis(PCA).The particle contacts and geometrical characteristics in 3D space were analyzed and summarized using statistical analyses.The results demonstrate that the main types of contact among the particles are face-face,face-angle,face-edge,edge-edge,edge-angle and angle-angle contacts for particle sizes less than 0.2 mm.When the particle sizes are greater than 0.2 mm,the contacts are effectively summarized as face-face,face-angle,face-edge,edge-edge,edge-angle,angle-angle,sphere-sphere,sphere-face,sphere-edge and sphere-angle contacts.The differences in porosity among the original sample,reconstructed sample and regularized sample are closely related to the water-swelling and water-disintegrable characteristics of granite residual soil.
文摘The chaotic nonlinear time series method is applied to analyze the sliver irregularity in textile processing.Because it unifies the system's determinacy and randomness,it seems more adaptive to describe the sliver irregularity than conventional methods.Firstly,the chaos character,i.e.fractal dimension,positive Lyapunov exponent,and state space parameters,including time delay and reconstruction dimension,are calculated respectively.As a result,a positive Lyapunov exponent and a fractal dimension are obtained,which demonstrates that the system is chaotic in fact.Secondly,both local linear forecast and global forecast models based on the reconstructed state are adopted to predict a segment part of the sliver irregularity series,which proves the validity of this analysis.Therefore,the sliver irregularity series shows the evidence of chaotic phenomena,and thus laying the theoretical foundation for analyzing and modeling the sliver irregularity series by applying the chaos theory,and providing a new way to understand the complexity of the sliver irregularity much better.
文摘In this paper, we mainly pay attention to the weighted sampling and reconstruction algorithm in lattice-invariant signal spaces. We give the reconstruction formula in lattice-invariant signal spaces, which is a generalization of former results in shift-invariant signal spaces. That is, we generalize and improve Aldroubi, Groechenig and Chen＇s results, respectively. So we obtain a general reconstruction algorithm in lattice-invariant signal spaces, which the signal spaces is sufficiently large to accommodate a large number of possible models. They are maybe useful for signal processing and communication theory.
