In this paper, we give a definition of the alternating iterative maximum likelihood estimator （AIMLE） which is a biased estimator. Furthermore we adjust the AIMLE to result in asymptotically unbiased and consistent ...In this paper, we give a definition of the alternating iterative maximum likelihood estimator （AIMLE） which is a biased estimator. Furthermore we adjust the AIMLE to result in asymptotically unbiased and consistent estimators by using a bootstrap iterative bias correction method as in Kuk （1995）. Two examples and simulation results reported illustrate the performance of the bias correction for AIMLE.展开更多
This paper discusses the problem of low-elevation target height estimation for multiple-input multiple-output(MIMO)radar in multipath environments.The beamspace compresses the data and is ideal for reducing the comput...This paper discusses the problem of low-elevation target height estimation for multiple-input multiple-output(MIMO)radar in multipath environments.The beamspace compresses the data and is ideal for reducing the computational burden of elevation estimation.To obtain the height parameter of the target accurately,we propose a height estimation method based on a beamspace joint alternating iterative(BJAI)algorithm in MIMO radar.This method mainly converts the reduced-dimensional MIMO radar element space data into beamspace data and whitens them to improve the reliability.Then,a simplified model is used to obtain the initial value of the elevation,and we combine the reflection coefficient and the target elevation angle for alternate estimation.Finally,we calculate the target height using the obtained elevation information.Simulation results verify that the proposed algorithm has high estimation accuracy and strong robustness.展开更多
This paper studies non-convex programming problems. It is known that, in statistical inference, many constrained estimation problems may be expressed as convex programming problems. However, in many practical problems...This paper studies non-convex programming problems. It is known that, in statistical inference, many constrained estimation problems may be expressed as convex programming problems. However, in many practical problems, the objective functions are not convex. In this paper, we give a definition of a semi-convex objective function and discuss the corresponding non-convex programming problems. A two-step iterative algorithm called the alternating iterative method is proposed for finding solutions for such problems. The method is illustrated by three examples in constrained estimation problems given in Sasabuchi et al. （Biometrika, 72, 465472 （1983））, Shi N. Z. （J. Multivariate Anal., 50, 282-293 （1994）） and El Barmi H. and Dykstra R. （Ann. Statist., 26, 1878 1893 （1998））.展开更多
A finite difference method is presented to simulate transverse vibrations of an axially moving string. By discretizing the governing equation and the equation of stress strain relation at different frictional knots, t...A finite difference method is presented to simulate transverse vibrations of an axially moving string. By discretizing the governing equation and the equation of stress strain relation at different frictional knots, two linear sparse finite difference equation systems are obtained. The two explicit difference schemes can be calculated alternatively, which make the computation much more efficient. The numerical method makes the nonlinear model easier to deal with and of truncation errors, O（△t^2 ＋ △x^2）. It also shows quite good stability for small initial values. Numerical examples are presented to demonstrate the efficiency and the stability of the algorithm, and dynamic analysis of a viscoelastic string is given by using the numerical results.展开更多
Regularization methods have been substantially applied in image restoration due to the ill-posedness of the image restoration problem.Different assumptions or priors on images are applied in the construction of image ...Regularization methods have been substantially applied in image restoration due to the ill-posedness of the image restoration problem.Different assumptions or priors on images are applied in the construction of image regularization methods.In recent years,matrix low-rank approximation has been successfully introduced in the image denoising problem and significant denoising effects have been achieved.Low-rank matrix minimization is an NP-hard problem and it is often replaced with the matrix’s weighted nuclear norm minimization(WNNM).The assumption that an image contains an extensive amount of self-similarity is the basis for the construction of the matrix low-rank approximation-based image denoising method.In this paper,we develop a model for image restoration using the sum of block matching matrices’weighted nuclear norm to be the regularization term in the cost function.An alternating iterative algorithm is designed to solve the proposed model and the convergence analyses of the algorithm are also presented.Numerical experiments show that the proposed method can recover the images much better than the existing regularization methods in terms of both recovered quantities and visual qualities.展开更多
A new restoration algorithm based on double loops and alternant iterations is proposed to restore the object image effectively from a few frames of turbulence-degraded images, Based on the double loops, the iterative ...A new restoration algorithm based on double loops and alternant iterations is proposed to restore the object image effectively from a few frames of turbulence-degraded images, Based on the double loops, the iterative relations for estimating the turbulent point spread function PSF and object image alternately are derived. The restoration experiments have been made on computers, showing that the proposed algorithm can obtain the optimal estimations of the object and the point spread function, with the feasibility and practicality of the proposed algorithm being convincing.展开更多
This paper proposes a decentralized robust two-stage dispatch framework for multi-area integrated electric-gas systems (M-IEGSs), with the consideration of Weymouth and linepack equations of tie-pipelines. The overall...This paper proposes a decentralized robust two-stage dispatch framework for multi-area integrated electric-gas systems (M-IEGSs), with the consideration of Weymouth and linepack equations of tie-pipelines. The overall methodology includes the equivalent conversion for the robust two-stage program and the decentralized optimization for the equivalent form. To obtain a tractable and equivalent counterpart for the robust two-stage program, a quadruple-loop procedure based on the column-and-constraint generation (C&CG) and the penalty convex-concave procedure (P-CCP) algorithms is derived, resulting in a series of mixed integer second-order cone programs (MISOCPs). Then, an improved I-ADMM is proposed to realize the decentralized optimization for MISOCPs. Moreover, three acceleration methods are devised to reduce the computation burden. Simulation results validate the effectiveness of the proposed methodology and corresponding acceleration measures.展开更多
To improve the quality of the illumination distribution,one novel indoor visible light communication(VLC)system,which is jointly assisted by the angle-diversity transceivers and simultaneous transmission and reflectio...To improve the quality of the illumination distribution,one novel indoor visible light communication(VLC)system,which is jointly assisted by the angle-diversity transceivers and simultaneous transmission and reflection-intelligent reflecting surface(STAR-IRS),has been proposed in this work.A Harris Hawks optimizer algorithm(HHOA)-based two-stage alternating iteration algorithm(TSAIA)is presented to jointly optimize the magnitude and uniformity of the received optical power.Besides,to demonstrate the superiority of the proposed strategy,several benchmark schemes are simulated and compared.Results showed that compared to other optimization strategies,the TSAIA scheme is more capable of balancing the average value and variance of the received optical power,when the maximal ratio combining(MRC)strategy is adopted at the receiver.Moreover,as the number of the STAR-IRS elements increases,the optical power variance of the system optimized by TSAIA scheme would become smaller while the average optical power would get larger.This study will benefit the design of received optical power distribution for indoor VLC systems.展开更多
In[3],Chan and Wong proposed to use total variational regularization for both images and point spread functions in blind deconvolution.Their experimental results show that the detail of the restored images cannot be r...In[3],Chan and Wong proposed to use total variational regularization for both images and point spread functions in blind deconvolution.Their experimental results show that the detail of the restored images cannot be recovered.In this paper,we consider images in Lipschitz spaces,and propose to use Lipschitz regularization for images and total variational regularization for point spread functions in blind deconvolution.Our experimental results show that such combination of Lipschitz and total variational regularization methods can recover both images and point spread functions quite well.展开更多
In this paper, spatial channel pairing(SCP) is introduced to coherent combining at the relay in relay networks. Closed-form solution to optimal coherent combining is derived. Given coherent combining, the approximate ...In this paper, spatial channel pairing(SCP) is introduced to coherent combining at the relay in relay networks. Closed-form solution to optimal coherent combining is derived. Given coherent combining, the approximate SCP solution is presented. Finally, an alternating iterative structure is developed. Simulation results and analysis show that, given the symbol error rate and data rate, the proposed alternating iterative structure achieves signal-to-noise ratio gains over existing schemes in maximum ratio combining(MRC) plus matched filter,MRC plus antenna selection, and distributed space-time block coding due to the use of SCP and iterative structure.展开更多
Consider the reconstruction of the complex refraction index of an object, which is immersed in a known homogeneous background, from the knowledge of scattered waves of the point sources outside of the object. We first...Consider the reconstruction of the complex refraction index of an object, which is immersed in a known homogeneous background, from the knowledge of scattered waves of the point sources outside of the object. We firstly establish the uniqueness for this inverse problem, which provides the theoretical basis for the reconstruction scheme. Then based on the contrast source inversion(CSI) method, we propose an algorithm determining the refraction index and the artificial wave sources alternately by a dynamic iterative scheme. The algorithm defines the iterates by solving a series of minimization problems with uniformly convex penalty terms, which are allowed to be non-smooth to include L1 and total variation like functionals, ensuring the reconstruction quality when the unknown refraction index has the special features such as sparsity and discontinuity. By choosing the regularizing parameter automatically, the algorithm is terminated in terms of discrepancy principle. The convergence property of the iterative sequence is rigorously proven. Numerical implementations demonstrate the validity of the proposed algorithm.展开更多
A numerical solution of the quadratic matrix equations associated with a nonsingular M-matrix by using the alternately linearized implicit iteration method is considered. An iteration method for computing a nonsingula...A numerical solution of the quadratic matrix equations associated with a nonsingular M-matrix by using the alternately linearized implicit iteration method is considered. An iteration method for computing a nonsingular M-matrix solution of the quadratic matrix equations is developed, and its corresponding theory is given. Some numerical examples are provided to show the efficiency of the new method.展开更多
基金Supported by the National Natural Science Foundation of China(Grant Nos.7117103571173029+3 种基金1093100211071035)the Program for New Century Excellent Talents(Grant No.NCET-10-315)Excellent TalentsProgram of Liaoning Educational Committee(Grant No.2008RC15)
文摘In this paper, we give a definition of the alternating iterative maximum likelihood estimator （AIMLE） which is a biased estimator. Furthermore we adjust the AIMLE to result in asymptotically unbiased and consistent estimators by using a bootstrap iterative bias correction method as in Kuk （1995）. Two examples and simulation results reported illustrate the performance of the bias correction for AIMLE.
基金Project supported by the National Natural Science Foundation of China(No.62271379)the National Radar Signal Processing Laboratory(No.KGJ202401)the Fundamental Research Funds for the Central Universities and the Innovation Fund of Xidian University(No.YJSJ24011)。
文摘This paper discusses the problem of low-elevation target height estimation for multiple-input multiple-output(MIMO)radar in multipath environments.The beamspace compresses the data and is ideal for reducing the computational burden of elevation estimation.To obtain the height parameter of the target accurately,we propose a height estimation method based on a beamspace joint alternating iterative(BJAI)algorithm in MIMO radar.This method mainly converts the reduced-dimensional MIMO radar element space data into beamspace data and whitens them to improve the reliability.Then,a simplified model is used to obtain the initial value of the elevation,and we combine the reflection coefficient and the target elevation angle for alternate estimation.Finally,we calculate the target height using the obtained elevation information.Simulation results verify that the proposed algorithm has high estimation accuracy and strong robustness.
基金the National Natural Science Foundation of China (Nos.10431010,10501005)Science Foundation for Young Teachers of NENU (No.20070103)
文摘This paper studies non-convex programming problems. It is known that, in statistical inference, many constrained estimation problems may be expressed as convex programming problems. However, in many practical problems, the objective functions are not convex. In this paper, we give a definition of a semi-convex objective function and discuss the corresponding non-convex programming problems. A two-step iterative algorithm called the alternating iterative method is proposed for finding solutions for such problems. The method is illustrated by three examples in constrained estimation problems given in Sasabuchi et al. （Biometrika, 72, 465472 （1983））, Shi N. Z. （J. Multivariate Anal., 50, 282-293 （1994）） and El Barmi H. and Dykstra R. （Ann. Statist., 26, 1878 1893 （1998））.
基金Project supported by the National Natural Science Foundation of China(No.10472060)the Natural Science Foundation of Shanghai Municipality(No.04ZR14058)the Shanghai Leading Academic Discipline Project(No.Y0103)
文摘A finite difference method is presented to simulate transverse vibrations of an axially moving string. By discretizing the governing equation and the equation of stress strain relation at different frictional knots, two linear sparse finite difference equation systems are obtained. The two explicit difference schemes can be calculated alternatively, which make the computation much more efficient. The numerical method makes the nonlinear model easier to deal with and of truncation errors, O（△t^2 ＋ △x^2）. It also shows quite good stability for small initial values. Numerical examples are presented to demonstrate the efficiency and the stability of the algorithm, and dynamic analysis of a viscoelastic string is given by using the numerical results.
基金This work is supported by the National Natural Science Foundation of China nos.11971215 and 11571156,MOE-LCSMSchool of Mathematics and Statistics,Hunan Normal University,Changsha,Hunan 410081,China.
文摘Regularization methods have been substantially applied in image restoration due to the ill-posedness of the image restoration problem.Different assumptions or priors on images are applied in the construction of image regularization methods.In recent years,matrix low-rank approximation has been successfully introduced in the image denoising problem and significant denoising effects have been achieved.Low-rank matrix minimization is an NP-hard problem and it is often replaced with the matrix’s weighted nuclear norm minimization(WNNM).The assumption that an image contains an extensive amount of self-similarity is the basis for the construction of the matrix low-rank approximation-based image denoising method.In this paper,we develop a model for image restoration using the sum of block matching matrices’weighted nuclear norm to be the regularization term in the cost function.An alternating iterative algorithm is designed to solve the proposed model and the convergence analyses of the algorithm are also presented.Numerical experiments show that the proposed method can recover the images much better than the existing regularization methods in terms of both recovered quantities and visual qualities.
文摘A new restoration algorithm based on double loops and alternant iterations is proposed to restore the object image effectively from a few frames of turbulence-degraded images, Based on the double loops, the iterative relations for estimating the turbulent point spread function PSF and object image alternately are derived. The restoration experiments have been made on computers, showing that the proposed algorithm can obtain the optimal estimations of the object and the point spread function, with the feasibility and practicality of the proposed algorithm being convincing.
文摘This paper proposes a decentralized robust two-stage dispatch framework for multi-area integrated electric-gas systems (M-IEGSs), with the consideration of Weymouth and linepack equations of tie-pipelines. The overall methodology includes the equivalent conversion for the robust two-stage program and the decentralized optimization for the equivalent form. To obtain a tractable and equivalent counterpart for the robust two-stage program, a quadruple-loop procedure based on the column-and-constraint generation (C&CG) and the penalty convex-concave procedure (P-CCP) algorithms is derived, resulting in a series of mixed integer second-order cone programs (MISOCPs). Then, an improved I-ADMM is proposed to realize the decentralized optimization for MISOCPs. Moreover, three acceleration methods are devised to reduce the computation burden. Simulation results validate the effectiveness of the proposed methodology and corresponding acceleration measures.
基金supported by the National Natural Science Foundation of China(No.62071365)the Key Research and Development Program of Shaanxi Province(No.2017ZDCXL-GY-06-02).
文摘To improve the quality of the illumination distribution,one novel indoor visible light communication(VLC)system,which is jointly assisted by the angle-diversity transceivers and simultaneous transmission and reflection-intelligent reflecting surface(STAR-IRS),has been proposed in this work.A Harris Hawks optimizer algorithm(HHOA)-based two-stage alternating iteration algorithm(TSAIA)is presented to jointly optimize the magnitude and uniformity of the received optical power.Besides,to demonstrate the superiority of the proposed strategy,several benchmark schemes are simulated and compared.Results showed that compared to other optimization strategies,the TSAIA scheme is more capable of balancing the average value and variance of the received optical power,when the maximal ratio combining(MRC)strategy is adopted at the receiver.Moreover,as the number of the STAR-IRS elements increases,the optical power variance of the system optimized by TSAIA scheme would become smaller while the average optical power would get larger.This study will benefit the design of received optical power distribution for indoor VLC systems.
基金This research is supported in part by RGC 7046/03P,7035/04P,7035/05P and HKBU FRGs.
文摘In[3],Chan and Wong proposed to use total variational regularization for both images and point spread functions in blind deconvolution.Their experimental results show that the detail of the restored images cannot be recovered.In this paper,we consider images in Lipschitz spaces,and propose to use Lipschitz regularization for images and total variational regularization for point spread functions in blind deconvolution.Our experimental results show that such combination of Lipschitz and total variational regularization methods can recover both images and point spread functions quite well.
基金Project supported by the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University,China(No.2013D02)the Open Research Fund of National Key Laboratory of Electromagnetic Environment,China Research Institute of Radiowave Propagation(No.201500013)+2 种基金the National Natural Science Foundation of China(Nos.61271230,61472190,and 61501238)the Research Fund for the Doctoral Program of Higher Education of China(No.20113219120019)the Foundation of Cloud Computing and Big Data for Agriculture and Forestry,China(No.117-612014063)
文摘In this paper, spatial channel pairing(SCP) is introduced to coherent combining at the relay in relay networks. Closed-form solution to optimal coherent combining is derived. Given coherent combining, the approximate SCP solution is presented. Finally, an alternating iterative structure is developed. Simulation results and analysis show that, given the symbol error rate and data rate, the proposed alternating iterative structure achieves signal-to-noise ratio gains over existing schemes in maximum ratio combining(MRC) plus matched filter,MRC plus antenna selection, and distributed space-time block coding due to the use of SCP and iterative structure.
基金supported by National Natural Science Foundation of China(Grant Nos.11421110002,11531005 and 11501102)National Science Foundation of Jiangsu Province(Grant No.BK20150594)
文摘Consider the reconstruction of the complex refraction index of an object, which is immersed in a known homogeneous background, from the knowledge of scattered waves of the point sources outside of the object. We firstly establish the uniqueness for this inverse problem, which provides the theoretical basis for the reconstruction scheme. Then based on the contrast source inversion(CSI) method, we propose an algorithm determining the refraction index and the artificial wave sources alternately by a dynamic iterative scheme. The algorithm defines the iterates by solving a series of minimization problems with uniformly convex penalty terms, which are allowed to be non-smooth to include L1 and total variation like functionals, ensuring the reconstruction quality when the unknown refraction index has the special features such as sparsity and discontinuity. By choosing the regularizing parameter automatically, the algorithm is terminated in terms of discrepancy principle. The convergence property of the iterative sequence is rigorously proven. Numerical implementations demonstrate the validity of the proposed algorithm.
基金This work was supported by the National Natural Science Foundation （No.11171337）, P. R. China.
文摘A numerical solution of the quadratic matrix equations associated with a nonsingular M-matrix by using the alternately linearized implicit iteration method is considered. An iteration method for computing a nonsingular M-matrix solution of the quadratic matrix equations is developed, and its corresponding theory is given. Some numerical examples are provided to show the efficiency of the new method.
