Recently,deep learning has yielded transformative success across optics and photonics,especially in optical metrology.Deep neural networks (DNNs) with a fully convolutional architecture (e.g.,U-Net and its derivatives...Recently,deep learning has yielded transformative success across optics and photonics,especially in optical metrology.Deep neural networks (DNNs) with a fully convolutional architecture (e.g.,U-Net and its derivatives) have been widely implemented in an end-to-end manner to accomplish various optical metrology tasks,such as fringe denoising,phase unwrapping,and fringe analysis.However,the task of training a DNN to accurately identify an image-to-image transform from massive input and output data pairs seems at best naive,as the physical laws governing the image formation or other domain expertise pertaining to the measurement have not yet been fully exploited in current deep learning practice.To this end,we introduce a physics-informed deep learning method for fringe pattern analysis (PI-FPA) to overcome this limit by integrating a lightweight DNN with a learning-enhanced Fourier transform profilometry (Le FTP) module.By parameterizing conventional phase retrieval methods,the Le FTP module embeds the prior knowledge in the network structure and the loss function to directly provide reliable phase results for new types of samples,while circumventing the requirement of collecting a large amount of high-quality data in supervised learning methods.Guided by the initial phase from Le FTP,the phase recovery ability of the lightweight DNN is enhanced to further improve the phase accuracy at a low computational cost compared with existing end-to-end networks.Experimental results demonstrate that PI-FPA enables more accurate and computationally efficient single-shot phase retrieval,exhibiting its excellent generalization to various unseen objects during training.The proposed PI-FPA presents that challenging issues in optical metrology can be potentially overcome through the synergy of physics-priors-based traditional tools and data-driven learning approaches,opening new avenues to achieve fast and accurate single-shot 3D imaging.展开更多
The interferogram of multiple-beam Fizeau fringe technique plays an important role to investigate the optical properties of fiber because this interferogram provides us with useful information which can used to determ...The interferogram of multiple-beam Fizeau fringe technique plays an important role to investigate the optical properties of fiber because this interferogram provides us with useful information which can used to determine the dispersion curve of the fiber sample. A common problem in any interferogram analysis is the accuracy in locating fringe centers (fringe skeleton). There are a lot of computer-aided algorithms, which depend on the interferogram types, used to fringe skeleton extraction of various digital interferogram. In this paper, as far as I know, a novel algorithm for fringe skeleton extraction of double bright fringe of multiple-beam Fizeau fringe is presented. The proposed algorithm based on using the different order of Fourier transform and the derivative-sign binary image. Also the proposed algorithm has been successfully tested by using a computer simulation fringe and an experimental pattern. The results are compared with the original interferogram and shown a good agreement.展开更多
Integrated transportation and land use studies are of major interest to planners because they consider the interaction between transportation development and land use change. Quantifying the impact of transport infras...Integrated transportation and land use studies are of major interest to planners because they consider the interaction between transportation development and land use change. Quantifying the impact of transport infrastructure on land use change is necessary for evaluating the role of transportation development in the process of land use and land cover change in the urban-rural fringe. Taking Qixia District of Nanjing City, Jiangsu Province, China as a typical urban-rural fringe area, this paper analyzes the patterns and charac- teristics of land use change along three major transportation arteries using land use data from 2000 and 2008. We examine the spatial differentiation and gradient of land use pattern around railway, expressway, and highway corridors to investigate whether land use change in the urban-rural fringe is related to distance from transportation arteries and to clarify the varying impacts of different forms of transport infrastructure on land use patterns. We find that construction land generally tends to be located close to major transportation arteries, and that railways have the most obvious influence on land use change in the urban-rural fringe, while the impact of expressways was not significant. We conclude that there exists a causal relationship between the presence of transportation arteries and land use change in the urban-rural fringe, but this relationship varies across different types of linear transnort infrastrncnlre.展开更多
As we already mentioned in [6], in Fourier analysis, since Fourier coefficients are computable and applicable, people have established many nice results by assuming monotonicty of the coefficients. Generally speaking,...As we already mentioned in [6], in Fourier analysis, since Fourier coefficients are computable and applicable, people have established many nice results by assuming monotonicty of the coefficients. Generally speaking, it became an important topic how to generalize monotonicity. In many studies the generalization follows by this way:展开更多
In the first paper of this series, we propose a multi-resolution theory of Fourier spectral estimates of finite duration signals. It is shown that multi-resolution capability, achieved without further observation, is ...In the first paper of this series, we propose a multi-resolution theory of Fourier spectral estimates of finite duration signals. It is shown that multi-resolution capability, achieved without further observation, is obtained by constructing multi-resolution signals from the only observed finite duration signal. Achieved resolutions meet bounds of the uncertainty principle (Heisenberg inequality). In the forthcoming parts of this series, multi-resolution Fourier performances are observed, applied to short signals and extended to time-frequency analysis.展开更多
In this paper, we report application procedures and observed results of multi-resolution Fourier analysis proposed in the first part of this series. Missing signal recovery derived from multi-resolution theory is deve...In this paper, we report application procedures and observed results of multi-resolution Fourier analysis proposed in the first part of this series. Missing signal recovery derived from multi-resolution theory is developed. It is shown that multi-resolution Fourier analysis enhances dramatically performances of Fourier spectra suffering limitations traced to implicit time windowing. Observed frequency resolutions, improvement of frequency estimations, contraction of spectral leakage and recovery of missing parts of finite duration signals are in accordance with theoretical predictions.展开更多
Different physical, mechanical and chemical processes, such as: ion implantation, oxidation, nitridation and others create on the surface of materials residual stress state, characterized by high level and strong gra...Different physical, mechanical and chemical processes, such as: ion implantation, oxidation, nitridation and others create on the surface of materials residual stress state, characterized by high level and strong gradient. X-ray diffraction method widely used for stress measurements has some difficulties in interpretation of experimental data, when the depth of X-ray penetration is compared with thickness of surface layer where inhomogeneous stress distribution is localized. Early it has been shown by authors that diffraction line broadening occurs when analyzed surface is characterized by strong gradient. The interest to study the diffraction line broadening is connected to the possibility of obtaining information about parameters of surface stress distribution. In the present paper the convolution and deconvolution concepts of Fourier analysis were applied to study X ray diffraction line broadening caused by surface stress gradients. Developed methodology allows determining of stress distribution in superficial layers of materials.展开更多
Photoelastic fringe patterns for stress analysis are investigated by use of hybrid technique and fringe phase shift method. The first one is a hybrid method which combines the conformal mapping technique and measured ...Photoelastic fringe patterns for stress analysis are investigated by use of hybrid technique and fringe phase shift method. The first one is a hybrid method which combines the conformal mapping technique and measured data away from the edge of a geometric discontinuity. Photoelastic data are hybridized with complex variable/mapping techniques to calculate photoelastic stress-field around a circular hole or an elliptical hole in plates under uniaxial tensile loading. This method determines full-field stresses in perforated finite tensile plates containing either a circular or an elliptical hole. The second one is a fringe phase shift method to separate isochromatics and isoclinics from photoelastic fringes of a circular disk under diametric compression by use of phase shift method. Digitally determined isochromatics and isoclinics are agreed well with those of manual measurements.展开更多
The fringe noises disrupt the precise measurement of the atom distribution in the process of the absorption images.The fringe removal algorithms have been proposed to reconstruct the ideal reference images of the abso...The fringe noises disrupt the precise measurement of the atom distribution in the process of the absorption images.The fringe removal algorithms have been proposed to reconstruct the ideal reference images of the absorption images to remove the fringe noises.However,the focus of these fringe removal algorithms is the association of the fringe removal performance with the physical systems,leaving the gap to analyze the workflows of different fringe removal algorithms.This survey reviews the fringe removal algorithms and classifies them into two categories:the imagedecomposition based methods and the deep-learning based methods.Then this survey draws the workflow details of two classical fringe removal algorithms,and conducts experiments on the abs DL ultracold image dataset.Experiments show that the singular value decomposition(SVD)method achieves outstanding performance,and the U-net method succeeds in implying the image inpainting idea.The main contribution of this survey is the interpretation of the fringe removal algorithms,which may help readers have a better understanding of the research status.展开更多
This paper investigates superconvergence properties of the direct discontinuous Galerkin(DDG)method with interface corrections and the symmetric DDG method for diffusion equations.We apply the Fourier analysis techniq...This paper investigates superconvergence properties of the direct discontinuous Galerkin(DDG)method with interface corrections and the symmetric DDG method for diffusion equations.We apply the Fourier analysis technique to symbolically compute eigenvalues and eigenvectors of the amplification matrices for both DDG methods with different coefficient settings in the numerical fluxes.Based on the eigen-structure analysis,we carry out error estimates of the DDG solutions,which can be decomposed into three parts:(i)dissipation errors of the physically relevant eigenvalue,which grow linearly with the time and are of order 2k for P^(k)(k=2,3)approximations;(ii)projection error from a special projection of the exact solution,which is decreasing over the time and is related to the eigenvector corresponding to the physically relevant eigenvalue;(iii)dissipative errors of non-physically relevant eigenvalues,which decay exponentially with respect to the spatial mesh sizeΔx.We observe that the errors are sensitive to the choice of the numerical flux coefficient for even degree P^(2)approximations,but are not for odd degree P^(3)approximations.Numerical experiments are provided to verify the theoretical results.展开更多
Fringe projection technique is a non-contact, full field 3-D shape measurement method. The object depth information is recorded in one or several deformed fringe patterns. The phase-shifting algorithm or the Fourier t...Fringe projection technique is a non-contact, full field 3-D shape measurement method. The object depth information is recorded in one or several deformed fringe patterns. The phase-shifting algorithm or the Fourier transform method can be used to extract the wrapped phase data. A phase unwrapping process is then applied to retrieve a continuous phase distribution, which represents the surface profile of the test object. In this paper, a quality-guided phase unwrapping approach is incorporated and two novel phase quality evaluation methods are proposed to facilitate the phase unwrapping process.展开更多
A carrier fringe techrtique for measuring surface deformation is described and verified by experiments. In contrast to conventional holography and fringe analysis, this holographic system is based on fibre optics and ...A carrier fringe techrtique for measuring surface deformation is described and verified by experiments. In contrast to conventional holography and fringe analysis, this holographic system is based on fibre optics and automatic spatial carrier fringe pattem analysis techniques Single-mode optic fibres are used to transfer both the object and reference beams. Carrier fringes are generated by simply translating the object beam between two exposures The Fourier transform is applied to the carrier fringe pattern to convert it to the spatial frequency domain, where it is processed The results are given for a centrally loaded disk, including a 3-D perspective plot of the out of plane deformation field, phase map, grey level map and contour map.展开更多
In order to attain good quality transfer function estimates from magnetotelluric field data(i.e.,smooth behavior and small uncertainties across all frequencies),we compare time series data processing with and without ...In order to attain good quality transfer function estimates from magnetotelluric field data(i.e.,smooth behavior and small uncertainties across all frequencies),we compare time series data processing with and without a multitaper approach for spectral estimation.There are several common ways to increase the reliability of the Fourier spectral estimation from experimental(noisy)data;for example to subdivide the experimental time series into segments,taper these segments(using single taper),perform the Fourier transform of the individual segments,and average the resulting spectra.展开更多
This paper considers the finite difference(FD)approximations of diffusion operators and the boundary treatments for different boundary conditions.The proposed schemes have the compact form and could achieve arbitrary ...This paper considers the finite difference(FD)approximations of diffusion operators and the boundary treatments for different boundary conditions.The proposed schemes have the compact form and could achieve arbitrary even order of accuracy.The main idea is to make use of the lower order compact schemes recursively,so as to obtain the high order compact schemes formally.Moreover,the schemes can be implemented efficiently by solving a series of tridiagonal systems recursively or the fast Fourier transform(FFT).With mathematical induction,the eigenvalues of the proposed differencing operators are shown to be bounded away from zero,which indicates the positive definiteness of the operators.To obtain numerical boundary conditions for the high order schemes,the simplified inverse Lax-Wendroff(SILW)procedure is adopted and the stability analysis is performed by the Godunov-Ryabenkii method and the eigenvalue spectrum visualization method.Various numerical experiments are provided to demonstrate the effectiveness and robustness of our algorithms.展开更多
Many domains, including communication, signal processing, and image processing, use the Fourier Transform as a mathematical tool for signal analysis. Although it can analyze signals with steady and transitory properti...Many domains, including communication, signal processing, and image processing, use the Fourier Transform as a mathematical tool for signal analysis. Although it can analyze signals with steady and transitory properties, it has limits. The Wavelet Packet Decomposition (WPD) is a novel technique that we suggest in this study as a way to improve the Fourier Transform and get beyond these drawbacks. In this experiment, we specifically considered the utilization of Daubechies level 4 for the wavelet transformation. The choice of Daubechies level 4 was motivated by several reasons. Daubechies wavelets are known for their compact support, orthogonality, and good time-frequency localization. By choosing Daubechies level 4, we aimed to strike a balance between preserving important transient information and avoiding excessive noise or oversmoothing in the transformed signal. Then we compared the outcomes of our suggested approach to the conventional Fourier Transform using a non-stationary signal. The findings demonstrated that the suggested method offered a more accurate representation of non-stationary and transient signals in the frequency domain. Our method precisely showed a 12% reduction in MSE and a 3% rise in PSNR for the standard Fourier transform, as well as a 35% decrease in MSE and an 8% increase in PSNR for voice signals when compared to the traditional wavelet packet decomposition method.展开更多
In many optical metrology techniques,fringe pattern analysis is the central algorithm for recovering the underlying phase distribution from the recorded fringe patterns.Despite extensive research efforts for decades,h...In many optical metrology techniques,fringe pattern analysis is the central algorithm for recovering the underlying phase distribution from the recorded fringe patterns.Despite extensive research efforts for decades,how to extract the desired phase information,with the highest possible accuracy,from the minimum number of fringe patterns remains one of the most challenging open problems.Inspired by recent successes of deep learning techniques for computer vision and other applications,we demonstrate for the first time,to our knowledge,that the deep neural networks can be trained to perform fringe analysis,which substantially enhances the accuracy of phase demodulation from a single fringe pattern.The effectiveness of the proposed method is experimentally verified using carrier fringe patterns under the scenario of fringe projection profilometry.Experimental results demonstrate its superior performance,in terms of high accuracy and edge-preserving,over two representative single-frame techniques:Fourier transform profilometry and windowed Fourier transform profilometry.展开更多
We focus on the study of multigrid methods with aggressive coarsening and polynomial smoothers for the solution of the linear systems corresponding to finite difference/element discretizations of the Laplace equation....We focus on the study of multigrid methods with aggressive coarsening and polynomial smoothers for the solution of the linear systems corresponding to finite difference/element discretizations of the Laplace equation.Using local Fourier analysis we determine automatically the optimal values for the parameters involved in defining the polynomial smoothers and achieve fast convergence of cycles with aggressive coarsening.We also present numerical tests supporting the theoretical results and the heuristic ideas.The methods we introduce are highly parallelizable and efficient multigrid algorithms on structured and semi-structured grids in two and three spatial dimensions.展开更多
基金funded by National Key Research and Development Program of China (2022YFB2804603,2022YFB2804604)National Natural Science Foundation of China (62075096,62205147,U21B2033)+7 种基金China Postdoctoral Science Foundation (2023T160318,2022M711630,2022M721619)Jiangsu Funding Program for Excellent Postdoctoral Talent (2022ZB254)The Leading Technology of Jiangsu Basic Research Plan (BK20192003)The“333 Engineering”Research Project of Jiangsu Province (BRA2016407)The Jiangsu Provincial“One belt and one road”innovation cooperation project (BZ2020007)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense (JSGP202105)Fundamental Research Funds for the Central Universities (30922010405,30921011208,30920032101,30919011222)National Major Scientific Instrument Development Project (62227818).
文摘Recently,deep learning has yielded transformative success across optics and photonics,especially in optical metrology.Deep neural networks (DNNs) with a fully convolutional architecture (e.g.,U-Net and its derivatives) have been widely implemented in an end-to-end manner to accomplish various optical metrology tasks,such as fringe denoising,phase unwrapping,and fringe analysis.However,the task of training a DNN to accurately identify an image-to-image transform from massive input and output data pairs seems at best naive,as the physical laws governing the image formation or other domain expertise pertaining to the measurement have not yet been fully exploited in current deep learning practice.To this end,we introduce a physics-informed deep learning method for fringe pattern analysis (PI-FPA) to overcome this limit by integrating a lightweight DNN with a learning-enhanced Fourier transform profilometry (Le FTP) module.By parameterizing conventional phase retrieval methods,the Le FTP module embeds the prior knowledge in the network structure and the loss function to directly provide reliable phase results for new types of samples,while circumventing the requirement of collecting a large amount of high-quality data in supervised learning methods.Guided by the initial phase from Le FTP,the phase recovery ability of the lightweight DNN is enhanced to further improve the phase accuracy at a low computational cost compared with existing end-to-end networks.Experimental results demonstrate that PI-FPA enables more accurate and computationally efficient single-shot phase retrieval,exhibiting its excellent generalization to various unseen objects during training.The proposed PI-FPA presents that challenging issues in optical metrology can be potentially overcome through the synergy of physics-priors-based traditional tools and data-driven learning approaches,opening new avenues to achieve fast and accurate single-shot 3D imaging.
文摘The interferogram of multiple-beam Fizeau fringe technique plays an important role to investigate the optical properties of fiber because this interferogram provides us with useful information which can used to determine the dispersion curve of the fiber sample. A common problem in any interferogram analysis is the accuracy in locating fringe centers (fringe skeleton). There are a lot of computer-aided algorithms, which depend on the interferogram types, used to fringe skeleton extraction of various digital interferogram. In this paper, as far as I know, a novel algorithm for fringe skeleton extraction of double bright fringe of multiple-beam Fizeau fringe is presented. The proposed algorithm based on using the different order of Fourier transform and the derivative-sign binary image. Also the proposed algorithm has been successfully tested by using a computer simulation fringe and an experimental pattern. The results are compared with the original interferogram and shown a good agreement.
基金Under the auspices of National Natural Science Foundation of China(No.40871255)Scientific Research Foundation of Graduate School of Nanjing University(No.2010CL12)
文摘Integrated transportation and land use studies are of major interest to planners because they consider the interaction between transportation development and land use change. Quantifying the impact of transport infrastructure on land use change is necessary for evaluating the role of transportation development in the process of land use and land cover change in the urban-rural fringe. Taking Qixia District of Nanjing City, Jiangsu Province, China as a typical urban-rural fringe area, this paper analyzes the patterns and charac- teristics of land use change along three major transportation arteries using land use data from 2000 and 2008. We examine the spatial differentiation and gradient of land use pattern around railway, expressway, and highway corridors to investigate whether land use change in the urban-rural fringe is related to distance from transportation arteries and to clarify the varying impacts of different forms of transport infrastructure on land use patterns. We find that construction land generally tends to be located close to major transportation arteries, and that railways have the most obvious influence on land use change in the urban-rural fringe, while the impact of expressways was not significant. We conclude that there exists a causal relationship between the presence of transportation arteries and land use change in the urban-rural fringe, but this relationship varies across different types of linear transnort infrastrncnlre.
基金Supported in part by Natural Science Foundation of China(No. 10471130).
文摘As we already mentioned in [6], in Fourier analysis, since Fourier coefficients are computable and applicable, people have established many nice results by assuming monotonicty of the coefficients. Generally speaking, it became an important topic how to generalize monotonicity. In many studies the generalization follows by this way:
文摘In the first paper of this series, we propose a multi-resolution theory of Fourier spectral estimates of finite duration signals. It is shown that multi-resolution capability, achieved without further observation, is obtained by constructing multi-resolution signals from the only observed finite duration signal. Achieved resolutions meet bounds of the uncertainty principle (Heisenberg inequality). In the forthcoming parts of this series, multi-resolution Fourier performances are observed, applied to short signals and extended to time-frequency analysis.
文摘In this paper, we report application procedures and observed results of multi-resolution Fourier analysis proposed in the first part of this series. Missing signal recovery derived from multi-resolution theory is developed. It is shown that multi-resolution Fourier analysis enhances dramatically performances of Fourier spectra suffering limitations traced to implicit time windowing. Observed frequency resolutions, improvement of frequency estimations, contraction of spectral leakage and recovery of missing parts of finite duration signals are in accordance with theoretical predictions.
文摘Different physical, mechanical and chemical processes, such as: ion implantation, oxidation, nitridation and others create on the surface of materials residual stress state, characterized by high level and strong gradient. X-ray diffraction method widely used for stress measurements has some difficulties in interpretation of experimental data, when the depth of X-ray penetration is compared with thickness of surface layer where inhomogeneous stress distribution is localized. Early it has been shown by authors that diffraction line broadening occurs when analyzed surface is characterized by strong gradient. The interest to study the diffraction line broadening is connected to the possibility of obtaining information about parameters of surface stress distribution. In the present paper the convolution and deconvolution concepts of Fourier analysis were applied to study X ray diffraction line broadening caused by surface stress gradients. Developed methodology allows determining of stress distribution in superficial layers of materials.
文摘Photoelastic fringe patterns for stress analysis are investigated by use of hybrid technique and fringe phase shift method. The first one is a hybrid method which combines the conformal mapping technique and measured data away from the edge of a geometric discontinuity. Photoelastic data are hybridized with complex variable/mapping techniques to calculate photoelastic stress-field around a circular hole or an elliptical hole in plates under uniaxial tensile loading. This method determines full-field stresses in perforated finite tensile plates containing either a circular or an elliptical hole. The second one is a fringe phase shift method to separate isochromatics and isoclinics from photoelastic fringes of a circular disk under diametric compression by use of phase shift method. Digitally determined isochromatics and isoclinics are agreed well with those of manual measurements.
基金founded by the National Natural Science Foundation of China(Grant No.62003020)。
文摘The fringe noises disrupt the precise measurement of the atom distribution in the process of the absorption images.The fringe removal algorithms have been proposed to reconstruct the ideal reference images of the absorption images to remove the fringe noises.However,the focus of these fringe removal algorithms is the association of the fringe removal performance with the physical systems,leaving the gap to analyze the workflows of different fringe removal algorithms.This survey reviews the fringe removal algorithms and classifies them into two categories:the imagedecomposition based methods and the deep-learning based methods.Then this survey draws the workflow details of two classical fringe removal algorithms,and conducts experiments on the abs DL ultracold image dataset.Experiments show that the singular value decomposition(SVD)method achieves outstanding performance,and the U-net method succeeds in implying the image inpainting idea.The main contribution of this survey is the interpretation of the fringe removal algorithms,which may help readers have a better understanding of the research status.
基金supported by the National Natural Science Foundation of China(Grant Nos.11871428 and 12071214)the Natural Science Foundation for Colleges and Universities of Jiangsu Province of China(Grant No.20KJB110011)+1 种基金supported by the National Science Foundation(Grant No.DMS-1620335)and the Simons Foundation(Grant No.637716)supported by the National Natural Science Foundation of China(Grant Nos.11871428 and 12272347).
文摘This paper investigates superconvergence properties of the direct discontinuous Galerkin(DDG)method with interface corrections and the symmetric DDG method for diffusion equations.We apply the Fourier analysis technique to symbolically compute eigenvalues and eigenvectors of the amplification matrices for both DDG methods with different coefficient settings in the numerical fluxes.Based on the eigen-structure analysis,we carry out error estimates of the DDG solutions,which can be decomposed into three parts:(i)dissipation errors of the physically relevant eigenvalue,which grow linearly with the time and are of order 2k for P^(k)(k=2,3)approximations;(ii)projection error from a special projection of the exact solution,which is decreasing over the time and is related to the eigenvector corresponding to the physically relevant eigenvalue;(iii)dissipative errors of non-physically relevant eigenvalues,which decay exponentially with respect to the spatial mesh sizeΔx.We observe that the errors are sensitive to the choice of the numerical flux coefficient for even degree P^(2)approximations,but are not for odd degree P^(3)approximations.Numerical experiments are provided to verify the theoretical results.
文摘Fringe projection technique is a non-contact, full field 3-D shape measurement method. The object depth information is recorded in one or several deformed fringe patterns. The phase-shifting algorithm or the Fourier transform method can be used to extract the wrapped phase data. A phase unwrapping process is then applied to retrieve a continuous phase distribution, which represents the surface profile of the test object. In this paper, a quality-guided phase unwrapping approach is incorporated and two novel phase quality evaluation methods are proposed to facilitate the phase unwrapping process.
文摘A carrier fringe techrtique for measuring surface deformation is described and verified by experiments. In contrast to conventional holography and fringe analysis, this holographic system is based on fibre optics and automatic spatial carrier fringe pattem analysis techniques Single-mode optic fibres are used to transfer both the object and reference beams. Carrier fringes are generated by simply translating the object beam between two exposures The Fourier transform is applied to the carrier fringe pattern to convert it to the spatial frequency domain, where it is processed The results are given for a centrally loaded disk, including a 3-D perspective plot of the out of plane deformation field, phase map, grey level map and contour map.
文摘In order to attain good quality transfer function estimates from magnetotelluric field data(i.e.,smooth behavior and small uncertainties across all frequencies),we compare time series data processing with and without a multitaper approach for spectral estimation.There are several common ways to increase the reliability of the Fourier spectral estimation from experimental(noisy)data;for example to subdivide the experimental time series into segments,taper these segments(using single taper),perform the Fourier transform of the individual segments,and average the resulting spectra.
基金supported by the NSFC grant 11801143J.Lu’s research is partially supported by the NSFC grant 11901213+3 种基金the National Key Research and Development Program of China grant 2021YFA1002900supported by the NSFC grant 11801140,12171177the Young Elite Scientists Sponsorship Program by Henan Association for Science and Technology of China grant 2022HYTP0009the Program for Young Key Teacher of Henan Province of China grant 2021GGJS067.
文摘This paper considers the finite difference(FD)approximations of diffusion operators and the boundary treatments for different boundary conditions.The proposed schemes have the compact form and could achieve arbitrary even order of accuracy.The main idea is to make use of the lower order compact schemes recursively,so as to obtain the high order compact schemes formally.Moreover,the schemes can be implemented efficiently by solving a series of tridiagonal systems recursively or the fast Fourier transform(FFT).With mathematical induction,the eigenvalues of the proposed differencing operators are shown to be bounded away from zero,which indicates the positive definiteness of the operators.To obtain numerical boundary conditions for the high order schemes,the simplified inverse Lax-Wendroff(SILW)procedure is adopted and the stability analysis is performed by the Godunov-Ryabenkii method and the eigenvalue spectrum visualization method.Various numerical experiments are provided to demonstrate the effectiveness and robustness of our algorithms.
文摘Many domains, including communication, signal processing, and image processing, use the Fourier Transform as a mathematical tool for signal analysis. Although it can analyze signals with steady and transitory properties, it has limits. The Wavelet Packet Decomposition (WPD) is a novel technique that we suggest in this study as a way to improve the Fourier Transform and get beyond these drawbacks. In this experiment, we specifically considered the utilization of Daubechies level 4 for the wavelet transformation. The choice of Daubechies level 4 was motivated by several reasons. Daubechies wavelets are known for their compact support, orthogonality, and good time-frequency localization. By choosing Daubechies level 4, we aimed to strike a balance between preserving important transient information and avoiding excessive noise or oversmoothing in the transformed signal. Then we compared the outcomes of our suggested approach to the conventional Fourier Transform using a non-stationary signal. The findings demonstrated that the suggested method offered a more accurate representation of non-stationary and transient signals in the frequency domain. Our method precisely showed a 12% reduction in MSE and a 3% rise in PSNR for the standard Fourier transform, as well as a 35% decrease in MSE and an 8% increase in PSNR for voice signals when compared to the traditional wavelet packet decomposition method.
基金This work was financially supported by the National Natural Science Foundation of China(61722506,61705105,and 11574152)the National Key R&D Program of China(2017YFF0106403)+2 种基金the Outstanding Youth Foundation of Jiangsu Province(BK20170034)the China Postdoctoral Science Foundation(2017M621747)the Jiangsu Planned Projects for Postdoctoral Research Funds(1701038A).
文摘In many optical metrology techniques,fringe pattern analysis is the central algorithm for recovering the underlying phase distribution from the recorded fringe patterns.Despite extensive research efforts for decades,how to extract the desired phase information,with the highest possible accuracy,from the minimum number of fringe patterns remains one of the most challenging open problems.Inspired by recent successes of deep learning techniques for computer vision and other applications,we demonstrate for the first time,to our knowledge,that the deep neural networks can be trained to perform fringe analysis,which substantially enhances the accuracy of phase demodulation from a single fringe pattern.The effectiveness of the proposed method is experimentally verified using carrier fringe patterns under the scenario of fringe projection profilometry.Experimental results demonstrate its superior performance,in terms of high accuracy and edge-preserving,over two representative single-frame techniques:Fourier transform profilometry and windowed Fourier transform profilometry.
文摘We focus on the study of multigrid methods with aggressive coarsening and polynomial smoothers for the solution of the linear systems corresponding to finite difference/element discretizations of the Laplace equation.Using local Fourier analysis we determine automatically the optimal values for the parameters involved in defining the polynomial smoothers and achieve fast convergence of cycles with aggressive coarsening.We also present numerical tests supporting the theoretical results and the heuristic ideas.The methods we introduce are highly parallelizable and efficient multigrid algorithms on structured and semi-structured grids in two and three spatial dimensions.