High-precision optical frequency measurement serves as a cornerstone of modern science and technology,enabling advancements in fields ranging from fundamental physics to quantum information technologies.Obtaining prec...High-precision optical frequency measurement serves as a cornerstone of modern science and technology,enabling advancements in fields ranging from fundamental physics to quantum information technologies.Obtaining precise photon frequencies,especially in the ultraviolet or even extreme ultraviolet regimes,is a key goal in both light–matter interaction experiments and engineering applications.High-order harmonic generation(HHG)is an ideal light source for producing such photons.In this work,we propose an optical temporal interference model(OTIM)that establishes an analogy with multi-slit Fraunhofer diffraction(MSFD)to manipulate fine-frequency photon generation by exploiting the temporal coherence of HHG processes.Our model provides a unified physical framework for three distinct non-integer HHG generation schemes:single-pulse,shaped-pulse,and laser pulse train approaches,which correspond to single-MSFD-like,double-MSFD-like,and multi-MSFD-like processes,respectively.Arbitrary non-integer HHG photons can be obtained using our scheme.Our approach provides a new perspective for accurately measuring and controlling photon frequencies in fields such as frequency comb technology,interferometry,and atomic clocks.展开更多
The high-order deformation effects in even-even^(246,248)No are investigated by means of pairing self-consistent WoodsSaxon-Strutinsky calculations using the potential-energy-surface(PES)approach in an extended deform...The high-order deformation effects in even-even^(246,248)No are investigated by means of pairing self-consistent WoodsSaxon-Strutinsky calculations using the potential-energy-surface(PES)approach in an extended deformation space(β_(2),β_(3),β_(4),β_(5),β_(6),β_(7),β_(8)).Based on the calculated two-dimensional projected energy maps and different potential energy curves,we found that the highly even-order deformations have an important impact on both the fission trajectory and energy minima,while the odd-order deformations,accompanying the even-order ones,primarily affect the fission path beyond the second barrier.Relative to the light actinide nuclei,the nuclear ground state changes to the superdeformed configuration,but the normally deformed minimum,as the low-energy shape isomer,may still be primarily responsible for enhancing nuclear stability and ensuring experimental accessibility in^(246,248)No.Our present investigation indicates the nonnegligible impact of high-order deformation effects along the fission valley and will be helpful for deepening the understanding of different deformation effects and deformation couplings in nuclei,especially in this neutron-deficient heavy-mass region.展开更多
Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectiv...Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.展开更多
With the availability of high-performance computing technology and the development of advanced numerical simulation methods, Computational Fluid Dynamics (CFD) is becoming more and more practical and efficient in engi...With the availability of high-performance computing technology and the development of advanced numerical simulation methods, Computational Fluid Dynamics (CFD) is becoming more and more practical and efficient in engineering. As one of the high-precision representative algorithms, the high-order Discontinuous Galerkin Method (DGM) has not only attracted widespread attention from scholars in the CFD research community, but also received strong development. However, when DGM is extended to high-speed aerodynamic flow field calculations, non-physical numerical Gibbs oscillations near shock waves often significantly affect the numerical accuracy and even cause calculation failure. Data driven approaches based on machine learning techniques can be used to learn the characteristics of Gibbs noise, which motivates us to use it in high-speed DG applications. To achieve this goal, labeled data need to be generated in order to train the machine learning models. This paper proposes a new method for denoising modeling of Gibbs phenomenon using a machine learning technique, the zero-shot learning strategy, to eliminate acquiring large amounts of CFD data. The model adopts a graph convolutional network combined with graph attention mechanism to learn the denoising paradigm from synthetic Gibbs noise data and generalize to DGM numerical simulation data. Numerical simulation results show that the Gibbs denoising model proposed in this paper can suppress the numerical oscillation near shock waves in the high-order DGM. Our work automates the extension of DGM to high-speed aerodynamic flow field calculations with higher generalization and lower cost.展开更多
In modern wireless communication and electromagnetic control,automatic modulationclassification(AMC)of orthogonal frequency division multiplexing(OFDM)signals plays animportant role.However,under Doppler frequency shi...In modern wireless communication and electromagnetic control,automatic modulationclassification(AMC)of orthogonal frequency division multiplexing(OFDM)signals plays animportant role.However,under Doppler frequency shift and complex multipath channel conditions,extracting discriminative features from high-order modulation signals and ensuring model inter-pretability remain challenging.To address these issues,this paper proposes a Fourier attention net-work(FAttNet),which combines an attention mechanism with a Fourier analysis network(FAN).Specifically,the method directly converts the input signal to the frequency domain using the FAN,thereby obtaining frequency features that reflect the periodic variations in amplitude and phase.Abuilt-in attention mechanism then automatically calculates the weights for each frequency band,focusing on the most discriminative components.This approach improves both classification accu-racy and model interpretability.Experimental validation was conducted via high-order modulationsimulation using an RF testbed.The results show that under three different Doppler frequencyshifts and complex multipath channel conditions,with a signal-to-noise ratio of 10 dB,the classifi-cation accuracy can reach 89.1%,90.4%and 90%,all of which are superior to the current main-stream methods.The proposed approach offers practical value for dynamic spectrum access and sig-nal security detection,and it makes important theoretical contributions to the application of deeplearning in complex electromagnetic signal recognition.展开更多
This paper is concerned with high-order neural networks with proportional delays. The proportional delay is a time-varying unbounded delay which is different from the constant delay, bounded time-varying delay and dis...This paper is concerned with high-order neural networks with proportional delays. The proportional delay is a time-varying unbounded delay which is different from the constant delay, bounded time-varying delay and distributed delay. By the nonlinear transformation yi(t) = ui( et)(i = 1, 2,..., n), we transform a class of high-order neural networks with proportional delays into a class of high-order neural networks with constant delays and timevarying coefficients. With the aid of Brouwer fixed point theorem and constructing the delay differential inequality, we obtain some delay-independent and delay-dependent sufficient conditions to ensure the existence, uniqueness and global exponential stability of equilibrium of the network. Two examples with their simulations are given to illustrate the theoretical findings. Our results are new and complement previously known results.展开更多
Networked-guarantee loans may cause systemic risk related concern for the government and banks in China.The prediction of the default of enterprise loans is a typical machine learning based classification problem, and...Networked-guarantee loans may cause systemic risk related concern for the government and banks in China.The prediction of the default of enterprise loans is a typical machine learning based classification problem, and the networked guarantee makes this problem very difficult to solve. As we know, a complex network is usually stored and represented by an adjacency matrix. It is a high-dimensional and sparse matrix, whereas machine-learning methods usually need lowdimensional dense feature representations. Therefore, in this paper, we propose a binary higher-order network embedding method to learn the low-dimensional representations of a guarantee network. We first set vertices of this heterogeneous economic network by binary roles (guarantor and guarantee), and then define high-order adjacent measures based on their roles and economic domain knowledge. Afterwards, we design a penalty parameter in the objective function to balance the importance of network structure and adjacency. We optimize it by negative sampling based gradient descent algorithms,which solve the limitation of stochastic gradient descent on weighted edges without compromising efficiency. Finally, we test our proposed method on three real-world network datasets. The result shows that this method outperforms other start-of-the-art algorithms for both classification accuracy and robustness, especially in a guarantee network.展开更多
In this paper, the global asymptotic stability analysis problem is considered for a class of stochastic high-order neural networks with tin.delays. Based on a Lyapunov-Krasovskii functional and the stochastic stabilit...In this paper, the global asymptotic stability analysis problem is considered for a class of stochastic high-order neural networks with tin.delays. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, several sufficient conditions are derived in order to guarantee the global asymptotic convergence of the equilibtium paint in the mean square. Investigation shows that the addressed stochastic highorder delayed neural networks are globally asymptotically stable in the mean square if there are solutions to some linear matrix inequalities （LMIs）. Hence, the global asymptotic stability of the studied stochastic high-order delayed neural networks can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed global stability criteria.展开更多
We theoretically investigate the high-order harmonic generation(HHG)of defect-free solids by solving the timedependent Schrodinger equation(TDSE).The results show that the harmonic intensity can be enhanced,harmonic o...We theoretically investigate the high-order harmonic generation(HHG)of defect-free solids by solving the timedependent Schrodinger equation(TDSE).The results show that the harmonic intensity can be enhanced,harmonic order can be extended,and modulation near the cutoff order becomes smaller for the second plateau by increasing the time delay.These effects are due to an increase of the electron population in higher energy bands,where the larger band gap allows electrons to release more energy,and the long electronic paths are suppressed.Additionally,we also investigate the HHG of defective solids by Bohmian trajectories(BT).It is found that the harmonic intensity of the second plateau can be further enhanced.Simultaneously,cutoff order is also extended due to Bohmian particles moving farther away from the defective zone.展开更多
A new oxidative N-heterocyclic carbene(NHC)-catalyzed high-order[7+3]annulation reaction ofγ-indolyl phenols as 1,7-dinucleophiles andα,β-alkynals with the aid of Sc(OTf)_(3)is reported,enabling the highly regiosel...A new oxidative N-heterocyclic carbene(NHC)-catalyzed high-order[7+3]annulation reaction ofγ-indolyl phenols as 1,7-dinucleophiles andα,β-alkynals with the aid of Sc(OTf)_(3)is reported,enabling the highly regioselective access to unprecedented polyarene-fused ten-membered lactams bearing a bridged aryl-aryl-indole scaffold in moderate to good yields.This protocol demonstrates a broad substrate scope,good compatibility with substituents and complete regioselectivity,providing an organocatalytic modular synthetic strategy for creating medium-sized lactams.展开更多
We investigate theoretically the effects of chirped laser pulses on high-order harmonic generation(HHG)from solids.We find that the harmonic spectra display redshifts for the driving laser pulses with negative chirp a...We investigate theoretically the effects of chirped laser pulses on high-order harmonic generation(HHG)from solids.We find that the harmonic spectra display redshifts for the driving laser pulses with negative chirp and blueshifts for those with positive chirp,which is due to the change in the instantaneous frequency of the driving laser for different chirped pulses.The analysis of crystal-momentum-resolved(k-resolved)HHG reveals that the frequency shifts are equal for the harmonics generated by different crystal momentum channels.The frequency shifts in the cutoff region are larger than those in the plateau region.With the increase of the absolute value of the chirp parameters,the frequency shifts of HHG become more significant,leading to the shifts from odd-to even-order harmonics.We also demonstrate that the frequency shifts of harmonic spectra are related to the duration of the chirped laser field,but are insensitive to the laser intensity and dephasing time.展开更多
Thermal expansion is crucial for various industrial processes and is increasingly the focus of research endeavors aimed at improving material performance.However,it is the continuous advancements in first-principles c...Thermal expansion is crucial for various industrial processes and is increasingly the focus of research endeavors aimed at improving material performance.However,it is the continuous advancements in first-principles calculations that have enabled researchers to understand the microscopic origins of thermal expansion.In this study,we propose a coefficient of thermal expansion(CTE)calculation scheme based on self-consistent phonon theory,incorporating the fourth-order anharmonicity.We selected four structures(Si,CaZrF_(6),SrTiO_(3),NaBr)to investigate high-order anharmonicity’s impact on their CTEs,based on bonding types.The results indicate that our method goes beyond the second-order quasi-harmonic approximation and the third-order perturbation theory,aligning closely with experimental data.Furthermore,we observed that an increase in the ionicity of the structures leads to a more pronounced influence of high-order anharmonicity on CTE,with this effect primarily manifesting in variations of the Grüneisen parameter.Our research provides a theoretical foundation for accurately predicting and regulating the thermal expansion behavior of materials.展开更多
An efficient and accurate scalar auxiliary variable(SAV)scheme for numerically solving nonlinear parabolic integro-differential equation(PIDE)is developed in this paper.The original equation is first transformed into ...An efficient and accurate scalar auxiliary variable(SAV)scheme for numerically solving nonlinear parabolic integro-differential equation(PIDE)is developed in this paper.The original equation is first transformed into an equivalent system,and the k-order backward differentiation formula(BDF k)and central difference formula are used to discretize the temporal and spatial derivatives,respectively.Different from the traditional discrete method that adopts full implicit or full explicit for the nonlinear integral terms,the proposed scheme is based on the SAV idea and can be treated semi-implicitly,taking into account both accuracy and effectiveness.Numerical results are presented to demonstrate the high-order convergence(up to fourth-order)of the developed schemes and it is computationally efficient in long-time computations.展开更多
Four optimal approaches of high-order finite-impulse response(FIR) digital filters were developed for designing four types filters using neural network algorithms. The solutions were presented as parallel algorithms t...Four optimal approaches of high-order finite-impulse response(FIR) digital filters were developed for designing four types filters using neural network algorithms. The solutions were presented as parallel algorithms to approximate the desired frequency response specification. Therefore, these methods avoid matrix inversion, and make a fast calculation of the filter’s coefficients possible. The convergence theorems of these proposed algorithms were presented and proved to illustrate them stable, and the implementation of these methods was described together with some design guidelines. The simulation results show that the ripples of the designed FIR filters are significantly little in the pass-band and stop-band, and the proposed algorithms are of fast convergence.展开更多
We present a comprehensive study on the role of various excited states in high-order harmonic generation of hydrogen atoms driven by a long-wavelength(1500 nm)laser field.By numerically solving the time-dependent Schr...We present a comprehensive study on the role of various excited states in high-order harmonic generation of hydrogen atoms driven by a long-wavelength(1500 nm)laser field.By numerically solving the time-dependent Schrodinger equation(TDSE)and performing a time-frequency analysis,we investigate the influence of individual excited states on the harmonic spectrum.Our results reveal that the 2s excited state primarily contributes to the enhancement of high-energy harmonic yields by facilitating long electron trajectories,while the 2p excited state predominantly suppresses harmonic yields in the lower-energy region(20th-50th orders)by altering the contributions of electron trajectories.Our results highlight the critical role of the excited states in the HHG process,even at longer laser wavelengths.展开更多
We performed real-time and real-space numerical simulations of high-order harmonic generation in the threedimensional structured molecule methane(CH_(4)) using time-dependent density functional theory. By irradiating ...We performed real-time and real-space numerical simulations of high-order harmonic generation in the threedimensional structured molecule methane(CH_(4)) using time-dependent density functional theory. By irradiating the methane molecule with an elliptically polarized laser pulse polarized in the x–y plane, we observed significant even-order harmonic emission in the z-direction. By analyzing the electron dynamics in the electric field and the multi-orbital effects of the molecule, we revealed that electron recombination near specific atoms in methane is the primary source of highorder harmonic generation in the z-direction. Furthermore, we identified the dominant molecular orbitals responsible for the enhancement of harmonics in this direction and demonstrated the critical role played by multi-orbital effects in this process.展开更多
The high-speed development of space defense technology demands a high state estimation capacity for spacecraft tracking methods.However,reentry flight is accompanied by complex flight environments,which brings to the ...The high-speed development of space defense technology demands a high state estimation capacity for spacecraft tracking methods.However,reentry flight is accompanied by complex flight environments,which brings to the uncertain,complex,and strongly coupled non-Gaussian detection noise.As a result,there are several intractable considerations on the problem of state estimation tasks corrupted by complex non-Gaussian outliers for non-linear dynamics systems in practical application.To address these issues,a new iterated rational quadratic(RQ)kernel high-order unscented Kalman filtering(IRQHUKF)algorithm via capturing the statistics to break through the limitations of the Gaussian assumption is proposed.Firstly,the characteristic analysis of the RQ kernel is investigated in detail,which is the first attempt to carry out an exploration of the heavy-tailed characteristic and the ability on capturing highorder moments of the RQ kernel.Subsequently,the RQ kernel method is first introduced into the UKF algorithm as an error optimization criterion,termed the iterated RQ kernel-UKF(RQ-UKF)algorithm by derived analytically,which not only retains the high-order moments propagation process but also enhances the approximation capacity in the non-Gaussian noise problem for its ability in capturing highorder moments and heavy-tailed characteristics.Meanwhile,to tackle the limitations of the Gaussian distribution assumption in the linearization process of the non-linear systems,the high-order Sigma Points(SP)as a subsidiary role in propagating the state high-order statistics is devised by the moments matching method to improve the RQ-UKF.Finally,to further improve the flexibility of the IRQ-HUKF algorithm in practical application,an adaptive kernel parameter is derived analytically grounded in the Kullback-Leibler divergence(KLD)method and parametric sensitivity analysis of the RQ kernel.The simulation results demonstrate that the novel IRQ-HUKF algorithm is more robust and outperforms the existing advanced UKF with respect to the kernel method in reentry vehicle tracking scenarios under various noise environments.展开更多
Due to the complex and changeable environment under water,the performance of traditional DOA estimation algorithms based on mathematical model,such as MUSIC,ESPRIT,etc.,degrades greatly or even some mistakes can be ma...Due to the complex and changeable environment under water,the performance of traditional DOA estimation algorithms based on mathematical model,such as MUSIC,ESPRIT,etc.,degrades greatly or even some mistakes can be made because of the mismatch between algorithm model and actual environment model.In addition,the neural network has the ability of generalization and mapping,it can consider the noise,transmission channel inconsistency and other factors of the objective environment.Therefore,this paper utilizes Back Propagation(BP)neural network as the basic framework of underwater DOA estimation.Furthermore,in order to improve the performance of DOA estimation of BP neural network,the following three improvements are proposed.(1)Aiming at the problem that the weight and threshold of traditional BP neural network converge slowly and easily fall into the local optimal value in the iterative process,PSO-BP-NN based on optimized particle swarm optimization(PSO)algorithm is proposed.(2)The Higher-order cumulant of the received signal is utilized to establish the training model.(3)A BP neural network training method for arbitrary number of sources is proposed.Finally,the effectiveness of the proposed algorithm is proved by comparing with the state-of-the-art algorithms and MUSIC algorithm.展开更多
A high-order fully actuated(HOFA)control method is developed for underactuated mechanical systems(UMSs)with model uncertainties and external disturbances.First,a model transformation is made from the original to a pse...A high-order fully actuated(HOFA)control method is developed for underactuated mechanical systems(UMSs)with model uncertainties and external disturbances.First,a model transformation is made from the original to a pseudo strict-feedback form,and an HOFA model is established by using the method of variable elimination.Then,a group of high-order extended state observers(ESOs)are designed to deal with model uncertainties and external disturbances.The HOFA model is further classified and decomposed to achieve output constraints within a finite time range,and a barrier function is designed by combining with a shift function.Additionally,an ESO-based HOFA tracking control strategy for UMS is proposed.Finally,a manipulator model is used to verify the effectiveness of the proposed control strategy.展开更多
An adaptive controller for a class of high-order MIMO nonlinear time-delay systems in block-triangular form is proposed in the paper.The radial basis function neural network is chosen to approximate the unknown nonlin...An adaptive controller for a class of high-order MIMO nonlinear time-delay systems in block-triangular form is proposed in the paper.The radial basis function neural network is chosen to approximate the unknown nonlinear ftmetions in the system dynamics at first.Lyapunov-Krasovskii fi.mctionals are used to compensate the influence of delay terms.Then an adaptive neural network output tracking controller is designed by using the back-stepping recursive method.Based on Lyapunov stability theory,the proposed controller can guarantee all closed-loop signals are globally,uniformly and ultimately bounded,while the output tracking is able to converge to a neighborhood of the origin.Finally,a simulation example is given to illustrate the correctness of the theoretical results.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.12304379)the Natural Science Foundation of Liaoning Province(Grant No.2024BS-269)the Guangdong Basic and Applied Basic Research Foundation(Grant No.025A1515011117)。
文摘High-precision optical frequency measurement serves as a cornerstone of modern science and technology,enabling advancements in fields ranging from fundamental physics to quantum information technologies.Obtaining precise photon frequencies,especially in the ultraviolet or even extreme ultraviolet regimes,is a key goal in both light–matter interaction experiments and engineering applications.High-order harmonic generation(HHG)is an ideal light source for producing such photons.In this work,we propose an optical temporal interference model(OTIM)that establishes an analogy with multi-slit Fraunhofer diffraction(MSFD)to manipulate fine-frequency photon generation by exploiting the temporal coherence of HHG processes.Our model provides a unified physical framework for three distinct non-integer HHG generation schemes:single-pulse,shaped-pulse,and laser pulse train approaches,which correspond to single-MSFD-like,double-MSFD-like,and multi-MSFD-like processes,respectively.Arbitrary non-integer HHG photons can be obtained using our scheme.Our approach provides a new perspective for accurately measuring and controlling photon frequencies in fields such as frequency comb technology,interferometry,and atomic clocks.
基金supported by the Natural Science Foundation of Henan Province(No.252300421478)the National Natural Science Foundation of China(Nos.11975209,U2032211,12075287)。
文摘The high-order deformation effects in even-even^(246,248)No are investigated by means of pairing self-consistent WoodsSaxon-Strutinsky calculations using the potential-energy-surface(PES)approach in an extended deformation space(β_(2),β_(3),β_(4),β_(5),β_(6),β_(7),β_(8)).Based on the calculated two-dimensional projected energy maps and different potential energy curves,we found that the highly even-order deformations have an important impact on both the fission trajectory and energy minima,while the odd-order deformations,accompanying the even-order ones,primarily affect the fission path beyond the second barrier.Relative to the light actinide nuclei,the nuclear ground state changes to the superdeformed configuration,but the normally deformed minimum,as the low-energy shape isomer,may still be primarily responsible for enhancing nuclear stability and ensuring experimental accessibility in^(246,248)No.Our present investigation indicates the nonnegligible impact of high-order deformation effects along the fission valley and will be helpful for deepening the understanding of different deformation effects and deformation couplings in nuclei,especially in this neutron-deficient heavy-mass region.
基金supported in part by the National Natural Science Foundation of China(62173255,62188101)Shenzhen Key Laboratory of Control Theory and Intelligent Systems(ZDSYS20220330161800001)
文摘Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.
基金co-supported by the Aeronautical Science Foundation of China(Nos.2018ZA52002,2019ZA052011).
文摘With the availability of high-performance computing technology and the development of advanced numerical simulation methods, Computational Fluid Dynamics (CFD) is becoming more and more practical and efficient in engineering. As one of the high-precision representative algorithms, the high-order Discontinuous Galerkin Method (DGM) has not only attracted widespread attention from scholars in the CFD research community, but also received strong development. However, when DGM is extended to high-speed aerodynamic flow field calculations, non-physical numerical Gibbs oscillations near shock waves often significantly affect the numerical accuracy and even cause calculation failure. Data driven approaches based on machine learning techniques can be used to learn the characteristics of Gibbs noise, which motivates us to use it in high-speed DG applications. To achieve this goal, labeled data need to be generated in order to train the machine learning models. This paper proposes a new method for denoising modeling of Gibbs phenomenon using a machine learning technique, the zero-shot learning strategy, to eliminate acquiring large amounts of CFD data. The model adopts a graph convolutional network combined with graph attention mechanism to learn the denoising paradigm from synthetic Gibbs noise data and generalize to DGM numerical simulation data. Numerical simulation results show that the Gibbs denoising model proposed in this paper can suppress the numerical oscillation near shock waves in the high-order DGM. Our work automates the extension of DGM to high-speed aerodynamic flow field calculations with higher generalization and lower cost.
基金supported by the National Natural Science Foundation of China(No.62027801).
文摘In modern wireless communication and electromagnetic control,automatic modulationclassification(AMC)of orthogonal frequency division multiplexing(OFDM)signals plays animportant role.However,under Doppler frequency shift and complex multipath channel conditions,extracting discriminative features from high-order modulation signals and ensuring model inter-pretability remain challenging.To address these issues,this paper proposes a Fourier attention net-work(FAttNet),which combines an attention mechanism with a Fourier analysis network(FAN).Specifically,the method directly converts the input signal to the frequency domain using the FAN,thereby obtaining frequency features that reflect the periodic variations in amplitude and phase.Abuilt-in attention mechanism then automatically calculates the weights for each frequency band,focusing on the most discriminative components.This approach improves both classification accu-racy and model interpretability.Experimental validation was conducted via high-order modulationsimulation using an RF testbed.The results show that under three different Doppler frequencyshifts and complex multipath channel conditions,with a signal-to-noise ratio of 10 dB,the classifi-cation accuracy can reach 89.1%,90.4%and 90%,all of which are superior to the current main-stream methods.The proposed approach offers practical value for dynamic spectrum access and sig-nal security detection,and it makes important theoretical contributions to the application of deeplearning in complex electromagnetic signal recognition.
基金Supported by National Natural Science Foundation of China under Grant Nos.61673008 and 11261010Project of High-level Innovative Talents of Guizhou Province([2016]5651)
文摘This paper is concerned with high-order neural networks with proportional delays. The proportional delay is a time-varying unbounded delay which is different from the constant delay, bounded time-varying delay and distributed delay. By the nonlinear transformation yi(t) = ui( et)(i = 1, 2,..., n), we transform a class of high-order neural networks with proportional delays into a class of high-order neural networks with constant delays and timevarying coefficients. With the aid of Brouwer fixed point theorem and constructing the delay differential inequality, we obtain some delay-independent and delay-dependent sufficient conditions to ensure the existence, uniqueness and global exponential stability of equilibrium of the network. Two examples with their simulations are given to illustrate the theoretical findings. Our results are new and complement previously known results.
文摘Networked-guarantee loans may cause systemic risk related concern for the government and banks in China.The prediction of the default of enterprise loans is a typical machine learning based classification problem, and the networked guarantee makes this problem very difficult to solve. As we know, a complex network is usually stored and represented by an adjacency matrix. It is a high-dimensional and sparse matrix, whereas machine-learning methods usually need lowdimensional dense feature representations. Therefore, in this paper, we propose a binary higher-order network embedding method to learn the low-dimensional representations of a guarantee network. We first set vertices of this heterogeneous economic network by binary roles (guarantor and guarantee), and then define high-order adjacent measures based on their roles and economic domain knowledge. Afterwards, we design a penalty parameter in the objective function to balance the importance of network structure and adjacency. We optimize it by negative sampling based gradient descent algorithms,which solve the limitation of stochastic gradient descent on weighted edges without compromising efficiency. Finally, we test our proposed method on three real-world network datasets. The result shows that this method outperforms other start-of-the-art algorithms for both classification accuracy and robustness, especially in a guarantee network.
文摘In this paper, the global asymptotic stability analysis problem is considered for a class of stochastic high-order neural networks with tin.delays. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, several sufficient conditions are derived in order to guarantee the global asymptotic convergence of the equilibtium paint in the mean square. Investigation shows that the addressed stochastic highorder delayed neural networks are globally asymptotically stable in the mean square if there are solutions to some linear matrix inequalities （LMIs）. Hence, the global asymptotic stability of the studied stochastic high-order delayed neural networks can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed global stability criteria.
基金supported by the Natural Science Foundation of Jilin Province of China(Grant No.20230101014JC)the Fundamental Research Funds for the Central Universities(Grant No.2572021BC05)the National Natural Science Foundation of China(Grant No.12374265)。
文摘We theoretically investigate the high-order harmonic generation(HHG)of defect-free solids by solving the timedependent Schrodinger equation(TDSE).The results show that the harmonic intensity can be enhanced,harmonic order can be extended,and modulation near the cutoff order becomes smaller for the second plateau by increasing the time delay.These effects are due to an increase of the electron population in higher energy bands,where the larger band gap allows electrons to release more energy,and the long electronic paths are suppressed.Additionally,we also investigate the HHG of defective solids by Bohmian trajectories(BT).It is found that the harmonic intensity of the second plateau can be further enhanced.Simultaneously,cutoff order is also extended due to Bohmian particles moving farther away from the defective zone.
基金National Natural Science Foundation of China(Nos.21971090 and 22271123)the NSF of Jiangsu Province(No.BK20230201)+1 种基金the Natural Science Foundation of Jiangsu Education Committee(No.22KJB150024)the Natural Science Foundation of Jiangsu Normal University(No.21XSRX010)。
文摘A new oxidative N-heterocyclic carbene(NHC)-catalyzed high-order[7+3]annulation reaction ofγ-indolyl phenols as 1,7-dinucleophiles andα,β-alkynals with the aid of Sc(OTf)_(3)is reported,enabling the highly regioselective access to unprecedented polyarene-fused ten-membered lactams bearing a bridged aryl-aryl-indole scaffold in moderate to good yields.This protocol demonstrates a broad substrate scope,good compatibility with substituents and complete regioselectivity,providing an organocatalytic modular synthetic strategy for creating medium-sized lactams.
基金Project supported by the Natural Science Foundation of Jilin Province of China(Grant No.20230101014JC)the National Natural Science Foundation of China(Grant No.12374265)。
文摘We investigate theoretically the effects of chirped laser pulses on high-order harmonic generation(HHG)from solids.We find that the harmonic spectra display redshifts for the driving laser pulses with negative chirp and blueshifts for those with positive chirp,which is due to the change in the instantaneous frequency of the driving laser for different chirped pulses.The analysis of crystal-momentum-resolved(k-resolved)HHG reveals that the frequency shifts are equal for the harmonics generated by different crystal momentum channels.The frequency shifts in the cutoff region are larger than those in the plateau region.With the increase of the absolute value of the chirp parameters,the frequency shifts of HHG become more significant,leading to the shifts from odd-to even-order harmonics.We also demonstrate that the frequency shifts of harmonic spectra are related to the duration of the chirped laser field,but are insensitive to the laser intensity and dephasing time.
基金Project supported by the National Natural Science Foundation of China(Grant No.62125402).
文摘Thermal expansion is crucial for various industrial processes and is increasingly the focus of research endeavors aimed at improving material performance.However,it is the continuous advancements in first-principles calculations that have enabled researchers to understand the microscopic origins of thermal expansion.In this study,we propose a coefficient of thermal expansion(CTE)calculation scheme based on self-consistent phonon theory,incorporating the fourth-order anharmonicity.We selected four structures(Si,CaZrF_(6),SrTiO_(3),NaBr)to investigate high-order anharmonicity’s impact on their CTEs,based on bonding types.The results indicate that our method goes beyond the second-order quasi-harmonic approximation and the third-order perturbation theory,aligning closely with experimental data.Furthermore,we observed that an increase in the ionicity of the structures leads to a more pronounced influence of high-order anharmonicity on CTE,with this effect primarily manifesting in variations of the Grüneisen parameter.Our research provides a theoretical foundation for accurately predicting and regulating the thermal expansion behavior of materials.
基金Supported by the National Natural Science Foundation of China(Grant Nos.12001210 and 12261103)the Natural Science Foundation of Henan(Grant No.252300420308)the Yunnan Fundamental Research Projects(Grant No.202301AT070117).
文摘An efficient and accurate scalar auxiliary variable(SAV)scheme for numerically solving nonlinear parabolic integro-differential equation(PIDE)is developed in this paper.The original equation is first transformed into an equivalent system,and the k-order backward differentiation formula(BDF k)and central difference formula are used to discretize the temporal and spatial derivatives,respectively.Different from the traditional discrete method that adopts full implicit or full explicit for the nonlinear integral terms,the proposed scheme is based on the SAV idea and can be treated semi-implicitly,taking into account both accuracy and effectiveness.Numerical results are presented to demonstrate the high-order convergence(up to fourth-order)of the developed schemes and it is computationally efficient in long-time computations.
基金Project (50677014) supported by the National Natural Science Foundation of China project (20060532002) supported by the Doctoral Special Fund of Ministry of Education, China+1 种基金project (NCET-04-0767) supported by the Program for New Century Excellent Talents in Universityprojects(06JJ2024, 03GKY3115, 04FJ2003, and 05GK2005) supported by the Foundation of Hunan Provincial Science and Technology
文摘Four optimal approaches of high-order finite-impulse response(FIR) digital filters were developed for designing four types filters using neural network algorithms. The solutions were presented as parallel algorithms to approximate the desired frequency response specification. Therefore, these methods avoid matrix inversion, and make a fast calculation of the filter’s coefficients possible. The convergence theorems of these proposed algorithms were presented and proved to illustrate them stable, and the implementation of these methods was described together with some design guidelines. The simulation results show that the ripples of the designed FIR filters are significantly little in the pass-band and stop-band, and the proposed algorithms are of fast convergence.
基金supported by the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi。
文摘We present a comprehensive study on the role of various excited states in high-order harmonic generation of hydrogen atoms driven by a long-wavelength(1500 nm)laser field.By numerically solving the time-dependent Schrodinger equation(TDSE)and performing a time-frequency analysis,we investigate the influence of individual excited states on the harmonic spectrum.Our results reveal that the 2s excited state primarily contributes to the enhancement of high-energy harmonic yields by facilitating long electron trajectories,while the 2p excited state predominantly suppresses harmonic yields in the lower-energy region(20th-50th orders)by altering the contributions of electron trajectories.Our results highlight the critical role of the excited states in the HHG process,even at longer laser wavelengths.
基金Project supported by the National Natural Science Foundation of China (Grant No. 12204214)the National Key Research and Development Program of China (Grant No. 2022YFE0134200)+1 种基金the Fundamental Research Funds for the Central Universities (Grant No. GK202207012), QCYRCXM-2022-241the Guangdong Basic and Applied Basic Research Foundation (Grant No. 2025A1515011117)。
文摘We performed real-time and real-space numerical simulations of high-order harmonic generation in the threedimensional structured molecule methane(CH_(4)) using time-dependent density functional theory. By irradiating the methane molecule with an elliptically polarized laser pulse polarized in the x–y plane, we observed significant even-order harmonic emission in the z-direction. By analyzing the electron dynamics in the electric field and the multi-orbital effects of the molecule, we revealed that electron recombination near specific atoms in methane is the primary source of highorder harmonic generation in the z-direction. Furthermore, we identified the dominant molecular orbitals responsible for the enhancement of harmonics in this direction and demonstrated the critical role played by multi-orbital effects in this process.
基金supported by the National Natural Science Foundation of China under Grant No.12072090.
文摘The high-speed development of space defense technology demands a high state estimation capacity for spacecraft tracking methods.However,reentry flight is accompanied by complex flight environments,which brings to the uncertain,complex,and strongly coupled non-Gaussian detection noise.As a result,there are several intractable considerations on the problem of state estimation tasks corrupted by complex non-Gaussian outliers for non-linear dynamics systems in practical application.To address these issues,a new iterated rational quadratic(RQ)kernel high-order unscented Kalman filtering(IRQHUKF)algorithm via capturing the statistics to break through the limitations of the Gaussian assumption is proposed.Firstly,the characteristic analysis of the RQ kernel is investigated in detail,which is the first attempt to carry out an exploration of the heavy-tailed characteristic and the ability on capturing highorder moments of the RQ kernel.Subsequently,the RQ kernel method is first introduced into the UKF algorithm as an error optimization criterion,termed the iterated RQ kernel-UKF(RQ-UKF)algorithm by derived analytically,which not only retains the high-order moments propagation process but also enhances the approximation capacity in the non-Gaussian noise problem for its ability in capturing highorder moments and heavy-tailed characteristics.Meanwhile,to tackle the limitations of the Gaussian distribution assumption in the linearization process of the non-linear systems,the high-order Sigma Points(SP)as a subsidiary role in propagating the state high-order statistics is devised by the moments matching method to improve the RQ-UKF.Finally,to further improve the flexibility of the IRQ-HUKF algorithm in practical application,an adaptive kernel parameter is derived analytically grounded in the Kullback-Leibler divergence(KLD)method and parametric sensitivity analysis of the RQ kernel.The simulation results demonstrate that the novel IRQ-HUKF algorithm is more robust and outperforms the existing advanced UKF with respect to the kernel method in reentry vehicle tracking scenarios under various noise environments.
基金Strategic Priority Research Program of Chinese Academy of Sciences,Grant No.XDA28040000,XDA28120000Natural Science Foundation of Shandong Province,Grant No.ZR2021MF094+2 种基金Key R&D Plan of Shandong Province,Grant No.2020CXGC010804Central Leading Local Science and Technology Development Special Fund Project,Grant No.YDZX2021122Science&Technology Specific Projects in Agricultural High-tech Industrial Demonstration Area of the Yellow River Delta,Grant No.2022SZX11。
文摘Due to the complex and changeable environment under water,the performance of traditional DOA estimation algorithms based on mathematical model,such as MUSIC,ESPRIT,etc.,degrades greatly or even some mistakes can be made because of the mismatch between algorithm model and actual environment model.In addition,the neural network has the ability of generalization and mapping,it can consider the noise,transmission channel inconsistency and other factors of the objective environment.Therefore,this paper utilizes Back Propagation(BP)neural network as the basic framework of underwater DOA estimation.Furthermore,in order to improve the performance of DOA estimation of BP neural network,the following three improvements are proposed.(1)Aiming at the problem that the weight and threshold of traditional BP neural network converge slowly and easily fall into the local optimal value in the iterative process,PSO-BP-NN based on optimized particle swarm optimization(PSO)algorithm is proposed.(2)The Higher-order cumulant of the received signal is utilized to establish the training model.(3)A BP neural network training method for arbitrary number of sources is proposed.Finally,the effectiveness of the proposed algorithm is proved by comparing with the state-of-the-art algorithms and MUSIC algorithm.
基金supported in part by the National Natural Science Foundation of China(62373208,62033003,62273105,U191140)Taishan Scholar Program of Shandong Province of China(tsqn202306218)+1 种基金the National Key Research and Development Program of China(2022YFB4703100)the National Natural Science Foundation of Shandong Province(ZR2024YQ032).
文摘A high-order fully actuated(HOFA)control method is developed for underactuated mechanical systems(UMSs)with model uncertainties and external disturbances.First,a model transformation is made from the original to a pseudo strict-feedback form,and an HOFA model is established by using the method of variable elimination.Then,a group of high-order extended state observers(ESOs)are designed to deal with model uncertainties and external disturbances.The HOFA model is further classified and decomposed to achieve output constraints within a finite time range,and a barrier function is designed by combining with a shift function.Additionally,an ESO-based HOFA tracking control strategy for UMS is proposed.Finally,a manipulator model is used to verify the effectiveness of the proposed control strategy.
文摘An adaptive controller for a class of high-order MIMO nonlinear time-delay systems in block-triangular form is proposed in the paper.The radial basis function neural network is chosen to approximate the unknown nonlinear ftmetions in the system dynamics at first.Lyapunov-Krasovskii fi.mctionals are used to compensate the influence of delay terms.Then an adaptive neural network output tracking controller is designed by using the back-stepping recursive method.Based on Lyapunov stability theory,the proposed controller can guarantee all closed-loop signals are globally,uniformly and ultimately bounded,while the output tracking is able to converge to a neighborhood of the origin.Finally,a simulation example is given to illustrate the correctness of the theoretical results.
