Actual engineering systems will be inevitably affected by uncertain factors.Thus,the Reliability-Based Multidisciplinary Design Optimization(RBMDO)has become a hotspot for recent research and application in complex en...Actual engineering systems will be inevitably affected by uncertain factors.Thus,the Reliability-Based Multidisciplinary Design Optimization(RBMDO)has become a hotspot for recent research and application in complex engineering system design.The Second-Order/First-Order Mean-Value Saddlepoint Approximate(SOMVSA/-FOMVSA)are two popular reliability analysis strategies that are widely used in RBMDO.However,the SOMVSA method can only be used efficiently when the distribution of input variables is Gaussian distribution,which significantly limits its application.In this study,the Gaussian Mixture Model-based Second-Order Mean-Value Saddlepoint Approximation(GMM-SOMVSA)is introduced to tackle above problem.It is integrated with the Collaborative Optimization(CO)method to solve RBMDO problems.Furthermore,the formula and procedure of RBMDO using GMM-SOMVSA-Based CO(GMM-SOMVSA-CO)are proposed.Finally,an engineering example is given to show the application of the GMM-SOMVSA-CO method.展开更多
This paper is concerned with a filtering problem for a class of nonlinear quantum stochastic systems with multichannel nondemolition measurements. The system-observation dynamics are governed by a Markovian Hudson-Par...This paper is concerned with a filtering problem for a class of nonlinear quantum stochastic systems with multichannel nondemolition measurements. The system-observation dynamics are governed by a Markovian Hudson-Parthasarathy quantum stochastic differential equation driven by quantum Wiener processes of bosonic fields in vacuum state. The Hamiltonian and system-field coupling operators, as functions of the system variables, are assumed to be represented in a Weyl quantization form. Using the Wigner-Moyal phase-space framework, we obtain a stochastic integro-differential equation for the posterior quasi-characteristic function （QCF） of the system conditioned on the measurements. This equation is a spatial Fourier domain representation of the Belavkin-Kushner-Stratonovich stochastic master equation driven by the innovation process associated with the measurements. We discuss a specific form of the posterior QCF dynamics in the case of linear system-field coupling and outline a Gaussian approximation of the posterior quantum state.展开更多
The Gaussian beam migration(GBM) is a steady imaging approach, which has high accuracy and efficiency. Its implementation mainly includes the traditional frequency domain and the recent popular space-time domain. Firs...The Gaussian beam migration(GBM) is a steady imaging approach, which has high accuracy and efficiency. Its implementation mainly includes the traditional frequency domain and the recent popular space-time domain. Firstly, we use the upward ray tracing strategy to get the backward wavefields. Then,we use the dominant frequency of the seismic data to simplify the imaginary traveltime calculation of the wavefields, which can cut down the Fourier transform number compared with the traditional GBM in the space-time domain. In addition, we choose an optimized parameter for the take-off angle increment of the up-going and down-going rays. These optimizations help us get an efficient space-time-domain acoustic GBM approach. Typical four examples show that the proposed method can significantly improve the computational efficiency up to one or even two orders of magnitude in different models with different model parameters and produce good imaging results with comparable accuracy and resolution with the traditional GBM in the space-time domain.展开更多
This paper analyzes the characteristic of matching efficiency between the fundamental mode of two kinds of optical waveguides and its Gaussian approximate field.Then, it presents a new method where the mode-field half...This paper analyzes the characteristic of matching efficiency between the fundamental mode of two kinds of optical waveguides and its Gaussian approximate field.Then, it presents a new method where the mode-field half-width of Caussian approximation for the fundamental mode should be defined according to the maximal matching efficiency method. The relationship between the mode-field half-width of the Gaussian approximate field obtained from the maximal matching efficiency and normalized frequency is studied; furthermore, two formulas of mode-field half-widths as a function of normalized frequency are proposed.展开更多
The pilotless frame synchronization approach and implementations of LDPC code are the crucial issue of LDPC decoder. The Maximum-A-Posteriori probability( MAP) decoder has a perfect frame synchronization error rate( F...The pilotless frame synchronization approach and implementations of LDPC code are the crucial issue of LDPC decoder. The Maximum-A-Posteriori probability( MAP) decoder has a perfect frame synchronization error rate( FSER) performance. In this paper,a theoretical derivation of the FSER performance of pilotless frame synchronization for LDPC code is presented. The FSER performance by theoretical analysis coincides well with that by simulation in additive white Gaussian channel and Rician fading channel. So it is estimated the FSER performance of an LDPC code by theoretical analysis can be used instead of the simulations which are much more time-consuming.展开更多
This paper researches end diffraction of slab waveguide and then matching efficiency between the far-field and its Gaussian approximate field is analyzed leads to a new definition of divergence half-angle. Finally, wh...This paper researches end diffraction of slab waveguide and then matching efficiency between the far-field and its Gaussian approximate field is analyzed leads to a new definition of divergence half-angle. Finally, why the far-field can be approximated by a Gaussian function is presented according to characteristic of beam propagation factor.展开更多
Based on the generalized diffraction integral formula and the idea that the angle misalignment of the cat-eye optical lens can be transformed into the displacement misalignment,an approximate analytical propagation fo...Based on the generalized diffraction integral formula and the idea that the angle misalignment of the cat-eye optical lens can be transformed into the displacement misalignment,an approximate analytical propagation formula for Gaussian beams through a cat-eye optical lens under large incidence angle condition is derived.Numerical results show that the diffraction effect of the apertures of the cat-eye optical lens becomes stronger along with the increase in incidence angle.The results are also compared with those from using an angular spectrum diffraction integral and experiment to illustrate the applicability and validity of our theoretical formula.It is shown that the approximate extent is good enough for the application of a cat-eye optical lens with a radius of 20 mm and a propagation distance of 100 m,and the approximate extent becomes better along with the increase in the radius of the cat-eye optical lens and the propagation distance.展开更多
Electromagnetic wave scattering from multilayers consisting of two two-layer Caussian rough surfaces with lossless media is investigated in the Kirchhoff approximation （KA）, with consideration of the shadowing effec...Electromagnetic wave scattering from multilayers consisting of two two-layer Caussian rough surfaces with lossless media is investigated in the Kirchhoff approximation （KA）, with consideration of the shadowing effects. The tapered incident wave is introduced into the classic KA, and the bistatic scattering coefficient is redetermined. The advantage of this method is that it is faster in computation than the exact numerical methods. The numerical results show that the bistatic scattering coefficient calculated in the KA is in good agreement with that obtained by using the method of moment （MOM） over a most angular range, which indicates the validity of the KA proposed in our paper. Finally, the effects of the relative permittivity, the root-mean-square （RMS） height, the correlative length, and the average height between the two interfaces on the bistatic scattering coefficient are discussed in detail.展开更多
Hybrid precoder design is a key technique providing better antenna gain and reduced hardware complexity in millimeter-wave(mmWave)massive multiple-input multiple-output(MIMO)systems.In this paper,Gaussian Mixture lear...Hybrid precoder design is a key technique providing better antenna gain and reduced hardware complexity in millimeter-wave(mmWave)massive multiple-input multiple-output(MIMO)systems.In this paper,Gaussian Mixture learned approximate message passing(GM-LAMP)network is presented for the design of optimal hybrid precoders suitable for mmWave Massive MIMO systems.Optimal hybrid precoder designs using a compressive sensing scheme such as orthogonal matching pursuit(OMP)and its derivatives results in high computational complexity when the dimensionality of the sparse signal is high.This drawback can be addressed using classical iterative algorithms such as approximate message passing(AMP),which has comparatively low computational complexity.The drawbacks of AMP algorithm are fixed shrinkage parameter and non-consideration of prior distribution of the hybrid precoders.In this paper,the fixed shrinkage parameter problem of the AMP algorithm is addressed using learned AMP(LAMP)network,and is further enhanced as GMLAMP network using the concept of Gaussian Mixture distribution of the hybrid precoders.The simula-tion results show that the proposed GM-LAMP network achieves optimal hybrid precoder design with enhanced achievable rates,better accuracy and low computational complexity compared to the existing algorithms.展开更多
This paper deals with the forward and backward problems for the nonlinear fractional pseudo-parabolic equation ut+(-Δ)^(s1)ut+β(-Δ)^(s2)u=F(u,x,t)subject o random Gaussian white noise for initial and final data.Und...This paper deals with the forward and backward problems for the nonlinear fractional pseudo-parabolic equation ut+(-Δ)^(s1)ut+β(-Δ)^(s2)u=F(u,x,t)subject o random Gaussian white noise for initial and final data.Under the suitable assumptions s1,s2andβ,we first show the ill-posedness of mild solutions for forward and backward problems in the sense of Hadamard,which are mainly driven by random noise.Moreover,we propose the Fourier truncation method for stabilizing the above ill-posed problems.We derive an error estimate between the exact solution and its regularized solution in an E‖·‖Hs22norm,and give some numerical examples illustrating the effect of above method.展开更多
提出基于知识度量的模糊粗糙c-均值聚类(fuzzy rough c-means based on the knowledge measure,KFRCM)算法。传统聚类算法在处理具有模糊边界的数据时存在一定的局限性,表现为对初始聚类中心较为敏感且在高维空间中效率较低。为解决上...提出基于知识度量的模糊粗糙c-均值聚类(fuzzy rough c-means based on the knowledge measure,KFRCM)算法。传统聚类算法在处理具有模糊边界的数据时存在一定的局限性,表现为对初始聚类中心较为敏感且在高维空间中效率较低。为解决上述问题,引入特征加权的知识度量,结合模糊隶属度函数与粗糙集近似算子,采用高斯核相似度以增强边界特性。实验采用14个数据集,实验结果表明,KFRCM算法的聚类准确性、稳定性和计算效率均优于6种主流聚类算法。该研究首次将知识度量与模糊粗糙聚类相结合,为开发更为可靠和适应性更强的聚类算法提供了新的思路和算法。展开更多
In this note, we consider stochastic heat equation with general additive Gaussian noise. Our aim is to derive some necessary and sufficient conditions on the Gaussian noise in order to solve the corresponding heat equ...In this note, we consider stochastic heat equation with general additive Gaussian noise. Our aim is to derive some necessary and sufficient conditions on the Gaussian noise in order to solve the corresponding heat equation. We investigate this problem invoking two differen t met hods, respectively, based on variance compu tations and on pat h-wise considerations in Besov spaces. We are going to see that, as anticipated, both approaches lead to the same necessary and sufficient condition on the noise. In addition, the path-wise approach brings out regularity results for the solution.展开更多
To overcome the limitations of conventional speech enhancement methods, such as inaccurate voice activity detector(VAD) and noise estimation, a novel speech enhancement algorithm based on the approximate message passi...To overcome the limitations of conventional speech enhancement methods, such as inaccurate voice activity detector(VAD) and noise estimation, a novel speech enhancement algorithm based on the approximate message passing(AMP) is adopted. AMP exploits the difference between speech and noise sparsity to remove or mute the noise from the corrupted speech. The AMP algorithm is adopted to reconstruct the clean speech efficiently for speech enhancement. More specifically, the prior probability distribution of speech sparsity coefficient is characterized by Gaussian-model, and the hyper-parameters of the prior model are excellently learned by expectation maximization(EM) algorithm. We utilize the k-nearest neighbor(k-NN) algorithm to learn the sparsity with the fact that the speech coefficients between adjacent frames are correlated. In addition, computational simulations are used to validate the proposed algorithm, which achieves better speech enhancement performance than other four baseline methods-Wiener filtering, subspace pursuit(SP), distributed sparsity adaptive matching pursuit(DSAMP), and expectation-maximization Gaussian-model approximate message passing(EM-GAMP) under different compression ratios and a wide range of signal to noise ratios(SNRs).展开更多
基金support from the National Natural Science Foundation of China(Grant No.52175130)the Sichuan Science and Technology Program(Grant No.2021YFS0336)+4 种基金the China Postdoctoral Science Foundation(Grant No.2021M700693)the 2021 Open Project of Failure Mechanics and Engineering Disaster Prevention,Key Lab of Sichuan Province(Grant No.FMEDP202104)the Fundamental Research Funds for the Central Universities(Grant No.ZYGX2019J035)the Sichuan Science and Technology Innovation Seedling Project Funding Project(Grant No.2021112)the Sichuan Special Equipment Inspection and Research Institute(YNJD-02-2020)are gratefully acknowledged.
文摘Actual engineering systems will be inevitably affected by uncertain factors.Thus,the Reliability-Based Multidisciplinary Design Optimization(RBMDO)has become a hotspot for recent research and application in complex engineering system design.The Second-Order/First-Order Mean-Value Saddlepoint Approximate(SOMVSA/-FOMVSA)are two popular reliability analysis strategies that are widely used in RBMDO.However,the SOMVSA method can only be used efficiently when the distribution of input variables is Gaussian distribution,which significantly limits its application.In this study,the Gaussian Mixture Model-based Second-Order Mean-Value Saddlepoint Approximation(GMM-SOMVSA)is introduced to tackle above problem.It is integrated with the Collaborative Optimization(CO)method to solve RBMDO problems.Furthermore,the formula and procedure of RBMDO using GMM-SOMVSA-Based CO(GMM-SOMVSA-CO)are proposed.Finally,an engineering example is given to show the application of the GMM-SOMVSA-CO method.
文摘This paper is concerned with a filtering problem for a class of nonlinear quantum stochastic systems with multichannel nondemolition measurements. The system-observation dynamics are governed by a Markovian Hudson-Parthasarathy quantum stochastic differential equation driven by quantum Wiener processes of bosonic fields in vacuum state. The Hamiltonian and system-field coupling operators, as functions of the system variables, are assumed to be represented in a Weyl quantization form. Using the Wigner-Moyal phase-space framework, we obtain a stochastic integro-differential equation for the posterior quasi-characteristic function （QCF） of the system conditioned on the measurements. This equation is a spatial Fourier domain representation of the Belavkin-Kushner-Stratonovich stochastic master equation driven by the innovation process associated with the measurements. We discuss a specific form of the posterior QCF dynamics in the case of linear system-field coupling and outline a Gaussian approximation of the posterior quantum state.
基金jointly supported by the National Key Research and Development Program of China (2019YFC0605503)the National Natural Science Foundation of China (41821002, 41922028,41874149)+1 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA14010303)the Major Scientific and Technological Projects of CNPC (ZD2019-183-003)。
文摘The Gaussian beam migration(GBM) is a steady imaging approach, which has high accuracy and efficiency. Its implementation mainly includes the traditional frequency domain and the recent popular space-time domain. Firstly, we use the upward ray tracing strategy to get the backward wavefields. Then,we use the dominant frequency of the seismic data to simplify the imaginary traveltime calculation of the wavefields, which can cut down the Fourier transform number compared with the traditional GBM in the space-time domain. In addition, we choose an optimized parameter for the take-off angle increment of the up-going and down-going rays. These optimizations help us get an efficient space-time-domain acoustic GBM approach. Typical four examples show that the proposed method can significantly improve the computational efficiency up to one or even two orders of magnitude in different models with different model parameters and produce good imaging results with comparable accuracy and resolution with the traditional GBM in the space-time domain.
基金Project supported by Natural Science Foundation of the Department of Science & Technology of Fujian Province of China (GrantNo 2007F5040)
文摘This paper analyzes the characteristic of matching efficiency between the fundamental mode of two kinds of optical waveguides and its Gaussian approximate field.Then, it presents a new method where the mode-field half-width of Caussian approximation for the fundamental mode should be defined according to the maximal matching efficiency method. The relationship between the mode-field half-width of the Gaussian approximate field obtained from the maximal matching efficiency and normalized frequency is studied; furthermore, two formulas of mode-field half-widths as a function of normalized frequency are proposed.
基金Supported by the National Natural Science Foundation of China(No.61271230,61472190)the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University(No.2013D02)the Open Research Fund of National Key Laboratory of Electromagnetic Environment,China Research Institute of Radiowave Propagation(No.201500013)
文摘The pilotless frame synchronization approach and implementations of LDPC code are the crucial issue of LDPC decoder. The Maximum-A-Posteriori probability( MAP) decoder has a perfect frame synchronization error rate( FSER) performance. In this paper,a theoretical derivation of the FSER performance of pilotless frame synchronization for LDPC code is presented. The FSER performance by theoretical analysis coincides well with that by simulation in additive white Gaussian channel and Rician fading channel. So it is estimated the FSER performance of an LDPC code by theoretical analysis can be used instead of the simulations which are much more time-consuming.
基金Supported by the Program of Fujian Education Department under Grant No. JB09069the Natural Science Fund of Fujian Province under Grant No. 2009J01275
文摘This paper researches end diffraction of slab waveguide and then matching efficiency between the far-field and its Gaussian approximate field is analyzed leads to a new definition of divergence half-angle. Finally, why the far-field can be approximated by a Gaussian function is presented according to characteristic of beam propagation factor.
基金the Fund of the National Defense Pre-Research Foundation of China under Grant Nos TY7131008 and 513210902.
文摘Based on the generalized diffraction integral formula and the idea that the angle misalignment of the cat-eye optical lens can be transformed into the displacement misalignment,an approximate analytical propagation formula for Gaussian beams through a cat-eye optical lens under large incidence angle condition is derived.Numerical results show that the diffraction effect of the apertures of the cat-eye optical lens becomes stronger along with the increase in incidence angle.The results are also compared with those from using an angular spectrum diffraction integral and experiment to illustrate the applicability and validity of our theoretical formula.It is shown that the approximate extent is good enough for the application of a cat-eye optical lens with a radius of 20 mm and a propagation distance of 100 m,and the approximate extent becomes better along with the increase in the radius of the cat-eye optical lens and the propagation distance.
基金supported by the National Natural Science Foundation of China (Grant No 60571058)the Specialized Research Fund for the Doctoral Program of Higher Education,China (Grant No 20070701010)
文摘Electromagnetic wave scattering from multilayers consisting of two two-layer Caussian rough surfaces with lossless media is investigated in the Kirchhoff approximation （KA）, with consideration of the shadowing effects. The tapered incident wave is introduced into the classic KA, and the bistatic scattering coefficient is redetermined. The advantage of this method is that it is faster in computation than the exact numerical methods. The numerical results show that the bistatic scattering coefficient calculated in the KA is in good agreement with that obtained by using the method of moment （MOM） over a most angular range, which indicates the validity of the KA proposed in our paper. Finally, the effects of the relative permittivity, the root-mean-square （RMS） height, the correlative length, and the average height between the two interfaces on the bistatic scattering coefficient are discussed in detail.
文摘Hybrid precoder design is a key technique providing better antenna gain and reduced hardware complexity in millimeter-wave(mmWave)massive multiple-input multiple-output(MIMO)systems.In this paper,Gaussian Mixture learned approximate message passing(GM-LAMP)network is presented for the design of optimal hybrid precoders suitable for mmWave Massive MIMO systems.Optimal hybrid precoder designs using a compressive sensing scheme such as orthogonal matching pursuit(OMP)and its derivatives results in high computational complexity when the dimensionality of the sparse signal is high.This drawback can be addressed using classical iterative algorithms such as approximate message passing(AMP),which has comparatively low computational complexity.The drawbacks of AMP algorithm are fixed shrinkage parameter and non-consideration of prior distribution of the hybrid precoders.In this paper,the fixed shrinkage parameter problem of the AMP algorithm is addressed using learned AMP(LAMP)network,and is further enhanced as GMLAMP network using the concept of Gaussian Mixture distribution of the hybrid precoders.The simula-tion results show that the proposed GM-LAMP network achieves optimal hybrid precoder design with enhanced achievable rates,better accuracy and low computational complexity compared to the existing algorithms.
基金supported by the Natural Science Foundation of China(11801108)the Natural Science Foundation of Guangdong Province(2021A1515010314)the Science and Technology Planning Project of Guangzhou City(202201010111)。
文摘This paper deals with the forward and backward problems for the nonlinear fractional pseudo-parabolic equation ut+(-Δ)^(s1)ut+β(-Δ)^(s2)u=F(u,x,t)subject o random Gaussian white noise for initial and final data.Under the suitable assumptions s1,s2andβ,we first show the ill-posedness of mild solutions for forward and backward problems in the sense of Hadamard,which are mainly driven by random noise.Moreover,we propose the Fourier truncation method for stabilizing the above ill-posed problems.We derive an error estimate between the exact solution and its regularized solution in an E‖·‖Hs22norm,and give some numerical examples illustrating the effect of above method.
文摘提出基于知识度量的模糊粗糙c-均值聚类(fuzzy rough c-means based on the knowledge measure,KFRCM)算法。传统聚类算法在处理具有模糊边界的数据时存在一定的局限性,表现为对初始聚类中心较为敏感且在高维空间中效率较低。为解决上述问题,引入特征加权的知识度量,结合模糊隶属度函数与粗糙集近似算子,采用高斯核相似度以增强边界特性。实验采用14个数据集,实验结果表明,KFRCM算法的聚类准确性、稳定性和计算效率均优于6种主流聚类算法。该研究首次将知识度量与模糊粗糙聚类相结合,为开发更为可靠和适应性更强的聚类算法提供了新的思路和算法。
基金supported by an NSERC granta startup fund of University of Albertasupported by the NSF grant DMS1613163
文摘In this note, we consider stochastic heat equation with general additive Gaussian noise. Our aim is to derive some necessary and sufficient conditions on the Gaussian noise in order to solve the corresponding heat equation. We investigate this problem invoking two differen t met hods, respectively, based on variance compu tations and on pat h-wise considerations in Besov spaces. We are going to see that, as anticipated, both approaches lead to the same necessary and sufficient condition on the noise. In addition, the path-wise approach brings out regularity results for the solution.
基金supported by National Natural Science Foundation of China(NSFC)(No.61671075)Major Program of National Natural Science Foundation of China(No.61631003)。
文摘To overcome the limitations of conventional speech enhancement methods, such as inaccurate voice activity detector(VAD) and noise estimation, a novel speech enhancement algorithm based on the approximate message passing(AMP) is adopted. AMP exploits the difference between speech and noise sparsity to remove or mute the noise from the corrupted speech. The AMP algorithm is adopted to reconstruct the clean speech efficiently for speech enhancement. More specifically, the prior probability distribution of speech sparsity coefficient is characterized by Gaussian-model, and the hyper-parameters of the prior model are excellently learned by expectation maximization(EM) algorithm. We utilize the k-nearest neighbor(k-NN) algorithm to learn the sparsity with the fact that the speech coefficients between adjacent frames are correlated. In addition, computational simulations are used to validate the proposed algorithm, which achieves better speech enhancement performance than other four baseline methods-Wiener filtering, subspace pursuit(SP), distributed sparsity adaptive matching pursuit(DSAMP), and expectation-maximization Gaussian-model approximate message passing(EM-GAMP) under different compression ratios and a wide range of signal to noise ratios(SNRs).
