We investigate an optimal harvesting problem for age-structured species,in which elder individuals are more competitive than younger ones,and the population is modeled by a highly nonlinear integro-partial differentia...We investigate an optimal harvesting problem for age-structured species,in which elder individuals are more competitive than younger ones,and the population is modeled by a highly nonlinear integro-partial differential equation with a global feedback boundary condition.The existence of optimal strategies is established by means of compactness and maximizing sequences,and the maximum principle obtained via an adjoint system,tangent-normal cones and a new continuity result.In addition,some numerical experiments are presented to show the effects of the price function and younger's weight on the optimal profits.展开更多
Forward modeling of seismic wave propagation is crucial for the realization of reverse time migration(RTM) and full waveform inversion(FWI) in attenuating transversely isotropic media. To describe the attenuation and ...Forward modeling of seismic wave propagation is crucial for the realization of reverse time migration(RTM) and full waveform inversion(FWI) in attenuating transversely isotropic media. To describe the attenuation and anisotropy properties of subsurface media, the pure-viscoacoustic anisotropic wave equations are established for wavefield simulations, because they can provide clear and stable wavefields. However, due to the use of several approximations in deriving the wave equation and the introduction of a fractional Laplacian approximation in solving the derived equation, the wavefields simulated by the previous pure-viscoacoustic tilted transversely isotropic(TTI) wave equations has low accuracy. To accurately simulate wavefields in media with velocity anisotropy and attenuation anisotropy, we first derive a new pure-viscoacoustic TTI wave equation from the exact complex-valued dispersion formula in viscoelastic vertical transversely isotropic(VTI) media. Then, we present the hybrid finite-difference and low-rank decomposition(HFDLRD) method to accurately solve our proposed pure-viscoacoustic TTI wave equation. Theoretical analysis and numerical examples suggest that our pure-viscoacoustic TTI wave equation has higher accuracy than previous pure-viscoacoustic TTI wave equations in describing q P-wave kinematic and attenuation characteristics. Additionally, the numerical experiment in a simple two-layer model shows that the HFDLRD technique outperforms the hybrid finite-difference and pseudo-spectral(HFDPS) method in terms of accuracy of wavefield modeling.展开更多
To explore the optimal evaluation mechanism of open-cast mining procedure,this paper takes the actual operation status of Huolinhe No.1 Open-cast Mine as the research basis,and makes a deep analysis of the four repres...To explore the optimal evaluation mechanism of open-cast mining procedure,this paper takes the actual operation status of Huolinhe No.1 Open-cast Mine as the research basis,and makes a deep analysis of the four representative mining procedures proposed by this mine.A detailed and comprehensive evaluation system is constructed using rank-sum ratio(RSR)method.The system covers 17 key indicators and aims to evaluate the advantages and disadvantages of each scheme in an all-round and multi-angle manner.Through the calculation and analysis by RSR method,the comprehensive evaluation of the four types of mining procedure schemes is carried out,and finally the secondary river improvement project is determined as the optimal mining implementation scheme,and the joint mining scheme of the south and north areas is the alternative strategy.The research results of this paper are objective,clear and definite,can not only reveal the effectiveness and feasibility of RSR method in solving the problem of open-cast mining procedure optimization,but also provide a strong technical support and decision-making basis for the future production development of Huolinhe No.1 Open-cast Mine.Thus,this study is expected to further promote the scientific and refined process of mining operations.展开更多
Low-rank matrix decomposition with first-order total variation(TV)regularization exhibits excellent performance in exploration of image structure.Taking advantage of its excellent performance in image denoising,we app...Low-rank matrix decomposition with first-order total variation(TV)regularization exhibits excellent performance in exploration of image structure.Taking advantage of its excellent performance in image denoising,we apply it to improve the robustness of deep neural networks.However,although TV regularization can improve the robustness of the model,it reduces the accuracy of normal samples due to its over-smoothing.In our work,we develop a new low-rank matrix recovery model,called LRTGV,which incorporates total generalized variation(TGV)regularization into the reweighted low-rank matrix recovery model.In the proposed model,TGV is used to better reconstruct texture information without over-smoothing.The reweighted nuclear norm and Li-norm can enhance the global structure information.Thus,the proposed LRTGV can destroy the structure of adversarial noise while re-enhancing the global structure and local texture of the image.To solve the challenging optimal model issue,we propose an algorithm based on the alternating direction method of multipliers.Experimental results show that the proposed algorithm has a certain defense capability against black-box attacks,and outperforms state-of-the-art low-rank matrix recovery methods in image restoration.展开更多
A propagator-based algorithm for direction of arrival(DOA)estimation of noncoherent one-dimensional(1-D)non-circular sources is presented such as binary phase shift keying(BPSK)and amplitude modulation(AM).The algorit...A propagator-based algorithm for direction of arrival(DOA)estimation of noncoherent one-dimensional(1-D)non-circular sources is presented such as binary phase shift keying(BPSK)and amplitude modulation(AM).The algorithm achieves DOA estimation through searching a 1-D spectrum,which is newly formed on the basis of the rank reduction criterion,and works well without knowledge of the non-circular phases.And then,a search-free implementation of the algorithm is also developed by using the polynomial rooting technique.According to the non-circular property,the algorithm can virtually enlarge the array aperture,thus significantly improving its estimation accuracy and enabling it to handle more sources than the number of sensors.Moreover,the algorithm requires no rotational invariance,so it can be applied to arbitrary array geometry and dispense with the high-complexity procedure of the eigen-decomposition of the correlation sample matrix.Finally,numerical simulations verify the performance and effectiveness of the proposed algorithm.展开更多
This paper aims at achieving a simultaneously sparse and low-rank estimator from the semidefinite population covariance matrices.We first benefit from a convex optimization which develops l1-norm penalty to encourage ...This paper aims at achieving a simultaneously sparse and low-rank estimator from the semidefinite population covariance matrices.We first benefit from a convex optimization which develops l1-norm penalty to encourage the sparsity and nuclear norm to favor the low-rank property.For the proposed estimator,we then prove that with high probability,the Frobenius norm of the estimation rate can be of order O(√((slgg p)/n))under a mild case,where s and p denote the number of nonzero entries and the dimension of the population covariance,respectively and n notes the sample capacity.Finally,an efficient alternating direction method of multipliers with global convergence is proposed to tackle this problem,and merits of the approach are also illustrated by practicing numerical simulations.展开更多
基金the National Natural Science Foundation of China(11871185)Zhejiang Provincial Natural Science Foundation of China(LY18A010010).
文摘We investigate an optimal harvesting problem for age-structured species,in which elder individuals are more competitive than younger ones,and the population is modeled by a highly nonlinear integro-partial differential equation with a global feedback boundary condition.The existence of optimal strategies is established by means of compactness and maximizing sequences,and the maximum principle obtained via an adjoint system,tangent-normal cones and a new continuity result.In addition,some numerical experiments are presented to show the effects of the price function and younger's weight on the optimal profits.
基金supported by the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)(No.2021QNLM020001)the Major Scientific and Technological Projects of Shandong Energy Group(No.SNKJ2022A06-R23)+1 种基金the Funds of Creative Research Groups of China(No.41821002)National Natural Science Foundation of China Outstanding Youth Science Fund Project(Overseas)(No.ZX20230152)。
文摘Forward modeling of seismic wave propagation is crucial for the realization of reverse time migration(RTM) and full waveform inversion(FWI) in attenuating transversely isotropic media. To describe the attenuation and anisotropy properties of subsurface media, the pure-viscoacoustic anisotropic wave equations are established for wavefield simulations, because they can provide clear and stable wavefields. However, due to the use of several approximations in deriving the wave equation and the introduction of a fractional Laplacian approximation in solving the derived equation, the wavefields simulated by the previous pure-viscoacoustic tilted transversely isotropic(TTI) wave equations has low accuracy. To accurately simulate wavefields in media with velocity anisotropy and attenuation anisotropy, we first derive a new pure-viscoacoustic TTI wave equation from the exact complex-valued dispersion formula in viscoelastic vertical transversely isotropic(VTI) media. Then, we present the hybrid finite-difference and low-rank decomposition(HFDLRD) method to accurately solve our proposed pure-viscoacoustic TTI wave equation. Theoretical analysis and numerical examples suggest that our pure-viscoacoustic TTI wave equation has higher accuracy than previous pure-viscoacoustic TTI wave equations in describing q P-wave kinematic and attenuation characteristics. Additionally, the numerical experiment in a simple two-layer model shows that the HFDLRD technique outperforms the hybrid finite-difference and pseudo-spectral(HFDPS) method in terms of accuracy of wavefield modeling.
文摘To explore the optimal evaluation mechanism of open-cast mining procedure,this paper takes the actual operation status of Huolinhe No.1 Open-cast Mine as the research basis,and makes a deep analysis of the four representative mining procedures proposed by this mine.A detailed and comprehensive evaluation system is constructed using rank-sum ratio(RSR)method.The system covers 17 key indicators and aims to evaluate the advantages and disadvantages of each scheme in an all-round and multi-angle manner.Through the calculation and analysis by RSR method,the comprehensive evaluation of the four types of mining procedure schemes is carried out,and finally the secondary river improvement project is determined as the optimal mining implementation scheme,and the joint mining scheme of the south and north areas is the alternative strategy.The research results of this paper are objective,clear and definite,can not only reveal the effectiveness and feasibility of RSR method in solving the problem of open-cast mining procedure optimization,but also provide a strong technical support and decision-making basis for the future production development of Huolinhe No.1 Open-cast Mine.Thus,this study is expected to further promote the scientific and refined process of mining operations.
基金Project supported by the National Natural Science Foundation of China(No.62072024)the Outstanding Youth Program of Beijing University of Civil Engineering and Architecture,China(No.JDJQ20220805)the Shenzhen Stability Support General Project(Type A),China(No.20200826104014001)。
文摘Low-rank matrix decomposition with first-order total variation(TV)regularization exhibits excellent performance in exploration of image structure.Taking advantage of its excellent performance in image denoising,we apply it to improve the robustness of deep neural networks.However,although TV regularization can improve the robustness of the model,it reduces the accuracy of normal samples due to its over-smoothing.In our work,we develop a new low-rank matrix recovery model,called LRTGV,which incorporates total generalized variation(TGV)regularization into the reweighted low-rank matrix recovery model.In the proposed model,TGV is used to better reconstruct texture information without over-smoothing.The reweighted nuclear norm and Li-norm can enhance the global structure information.Thus,the proposed LRTGV can destroy the structure of adversarial noise while re-enhancing the global structure and local texture of the image.To solve the challenging optimal model issue,we propose an algorithm based on the alternating direction method of multipliers.Experimental results show that the proposed algorithm has a certain defense capability against black-box attacks,and outperforms state-of-the-art low-rank matrix recovery methods in image restoration.
基金supported in part by Funding for Outstanding Doctoral Dissertation in Nanjing University of Aeronautics and Astronautics (No. BCXJ15 03)the Funding of Jiangsu Innovation Program for Graduate Education (No. KYLX15_0281)the Fundamental Research Funds for the Central Universities
文摘A propagator-based algorithm for direction of arrival(DOA)estimation of noncoherent one-dimensional(1-D)non-circular sources is presented such as binary phase shift keying(BPSK)and amplitude modulation(AM).The algorithm achieves DOA estimation through searching a 1-D spectrum,which is newly formed on the basis of the rank reduction criterion,and works well without knowledge of the non-circular phases.And then,a search-free implementation of the algorithm is also developed by using the polynomial rooting technique.According to the non-circular property,the algorithm can virtually enlarge the array aperture,thus significantly improving its estimation accuracy and enabling it to handle more sources than the number of sensors.Moreover,the algorithm requires no rotational invariance,so it can be applied to arbitrary array geometry and dispense with the high-complexity procedure of the eigen-decomposition of the correlation sample matrix.Finally,numerical simulations verify the performance and effectiveness of the proposed algorithm.
基金The work was supported in part by the National Natural Science Foundation of China(Nos.11431002,11171018,71271021,11301022).
文摘This paper aims at achieving a simultaneously sparse and low-rank estimator from the semidefinite population covariance matrices.We first benefit from a convex optimization which develops l1-norm penalty to encourage the sparsity and nuclear norm to favor the low-rank property.For the proposed estimator,we then prove that with high probability,the Frobenius norm of the estimation rate can be of order O(√((slgg p)/n))under a mild case,where s and p denote the number of nonzero entries and the dimension of the population covariance,respectively and n notes the sample capacity.Finally,an efficient alternating direction method of multipliers with global convergence is proposed to tackle this problem,and merits of the approach are also illustrated by practicing numerical simulations.
