One way domain decomposition method with second order transmission conditions for solving electromagnetic wave problems

Non-overlapping domain decomposition (DD) methods with complex first order Robin-type transmission conditions (TCs) provide an efficient iterative solution for Maxwell’s equation. Unfortunately, the first order TCs do not effectively account for some eigenmodes of the system matrix, which limits the scalability of the methods. In this work, we examine two TCs with a second order transverse derivative to improve the method’s performance. A detailed convergence analysis of the two TCs is presented. We then investigate the use of the two second order TCs in non-conformal and non-overlapping one way DD methods. Numerical results illustrate the effectiveness of the proposed methods on some model problems and on several problems of practical interest.     

A boundary-based net-exchange Monte Carlo method for absorbing and scattering thick media

A boundary-based net-exchange Monte Carlo method was introduced (JQSRT 74 (2001) 563) that allows to bypass the difficulties encountered by standard Monte Carlo algorithms in the limit of optically thick absorption (and/or for quasi-isothermal configurations). With the present paper, this method is extended to scattering media. Developments are fully 3D, but illustrations are presented for plane parallel configuration. Compared to standard Monte Carlo algorithms, convergence qualities have been improved over a wide range of absorption and scattering optical thicknesses. The proposed algorithm still encounters a convergence difficulty in the case of optically thick, highly scattering media.     

三维非匹配网格上的扩散方程数值求解

将子网格剖分的支撑算子方法,拓展应用于三维非匹配网格上的扩散方程求解.算例表明该方法在正交非匹配网格上能够精确获得线性解;在一般非匹配网格上可以达到二阶精度;在求解曲面网格和节点不共面网格时,精度比平面近似的方法要高,也可以达到2阶精度,同时也适合求解含有物质界面的混合介质网格.     

几种自适应IIR陷波器的复数算法及其应用

在自适应IIR陷波器实数算法的基础上,本文提出了三种基于梯度的自适应IIR陷波器的复数算法,并进行了仿真比较。结果表明,这三种复数算法均可检测复信号,并估计信号频率,其中"改进的"简化格型IIR陷波器复数算法收敛速度快、低信噪比下稳定性能好。湖上试验表明该算法不仅实时性好,而且在低信噪比下的检测效果令人满意。     

旁瓣约束下期望主瓣幅度响应迭代波束设计

研究了旁瓣约束下的期望主瓣幅度逼近问题,其包含双边绝对值不等式结构,为非凸波束设计问题。针对传统的多约束优化算法难以处理非凸结构,提出了两种迭代算法。一种对原优化问题作局域线性近似,将非凸约束转换为仿射约束,进而迭代局部二阶锥规划问题求解原问题。另一种通过引入辅助变量构建增广拉格朗日函数,将加权向量与各约束解耦合,交替迭代求解关于原变量、主瓣辅助变量与旁瓣辅助变量的三个子优化问题以给出初始非凸问题的解。针对子优化问题,通过灵活运用拉格朗日乘子技术构建了低复杂度求解方案。采用仿真和实测阵列流形验证设计效果,结果表明,所提两种迭代算法可实现主瓣幅度逼近,合成平顶波束图,且对阵型无依赖性。交替迭代法耗时显著低于迭代二阶锥规划法。      

Modified Gerchberg–Saxton (G-S) Algorithm and Its Application

The Gerchberg–Saxton (G-S) algorithm is a phase retrieval algorithm that is widely used in beam shaping and optical information processing. However, the G-S algorithm has difficulty obtaining the exact solution after iterating, and an approximate solution is often obtained. In this paper, we propose a series of modified G-S algorithms based on the Fresnel transform domain, including the single-phase retrieval (SPR) algorithm, the double-phase retrieval (DPR) algorithm, and the multiple-phase retrieval (MPR) algorithm. The analysis results show that the convergence of the SPR algorithm is better than that of the G-S algorithm, but the exact solution is not obtained. The DPR and MPR algorithms have good convergence and can obtain exact solutions; that is, the information is recovered losslessly. We discuss the security advantages and verification reliability of the proposed algorithms in image encryption. A multiple-image encryption scheme is proposed, in which n plaintexts can be recovered from n ciphertexts, which greatly improves the efficiency of the system. Finally, the proposed algorithms are compared with the current phase retrieval algorithms, and future applications are discussed. We hope that our research can provide new ideas for the application of the G-S algorithm.     

双扩展水声信道的时延多普勒域稀疏估计

利用双扩展水声信道在时延-多普勒域存在的稀疏结构,将信道估计转化为压缩感知框架下的稀疏恢复问题可改善估计性能。但是,稀疏恢复经典方法如l_1范数、近似l₀范数无法适应水声信道时延-多普勒域稀疏度的动态变化,而匹配追踪(Matching pursuit,MP)、正交匹配追踪(Orthogonal Matching Pursuit,OMP)等贪婪类算法则存在着易进入局部最优解、二维搜索导致运算复杂度高等问题。提出在时延-多普勒域稀疏恢复的目标函数中引入非均匀范数约束(Non-uniform Norm Constraint,NNC),即在时延-多普勒域信道响应中根据每个时延-多普勒域位置的幅值分别分配为l₀或l₁范数约束,因而可通过不同范数约束组合的方式适应不同的时延-多普勒域稀疏度;同时,通过对非均匀范数代价函数进行梯度下降迭代求解并将梯度解投影至解空间推导了非均匀范数稀疏恢复的迭代求解方法,从而实现双扩展水声信道时延-多普勒估计。数值仿真和实验数据处理表明该算法相对经典方法有较明显的性能改善。通过仿真、海上水声通信实验结果可获取结论,利用时延-多普勒域稀疏特性的信道估计方法结合均衡器可有效提高双扩展信道条件下的水声通信性能。      

基于Dual-Mode MCMA+DD双模式盲均衡算法研究*

为了兼顾误差性能和收敛速度,研究了将双模修正常量模算法和判决引导算法有机结合的双模式盲均衡算法.该算法在收敛初期采用双模修正常量模算法调整均衡器,然后根据判决条件自动切换到判决引导算法,最终实现信道的盲均衡.仿真结果表明：此算法收敛速度快、稳态误差小,并能在去除码间干扰的同时纠正信道固有的相位旋转,具有很好的实用性.     

具有不同时延的多智能体系统一致性分析

针对有向加权且存在全局可达点的静态网络拓扑, 考虑了同时具有通信时延和输入时延的一阶、二阶智能体系统的运动一致性问题. 基于广义Nyquist准则与频域控制理论的方法, 分析并得到了网络中所有智能体渐进收敛到一致状态的充分条件. 通过该条件发现一致性的达到只与系统的耦合强度、智能体的输入时延以及各自的连接状态信息有关, 与通信时延无关. 但是, 通信时延的存在却要影响系统的动态特性. 仿真实验结果进一步验证了理论分析所得结论的正确性.     

Time Step Validation Method Research for Low-Prandtl Number Fluid Numerical Simulation

The stability condition of Courant number and diffusion number is proved for an SGSD (stability guaranteed second-order difference) scheme by von Neumann method in implicit and explicit discretization of the one-dimensional convection and diffusion terms. Then, a series of numerical simulations of fluid flow and heat transfer based on two-dimensional unsteady state model is used to study the combined natural and MHD (magnetohydrodynamics) convection in a Joule-heated cavity using the finite volume methods, for the fluid of Pr = 0.01, also we use an SGSD scheme and IDEAL (inner doubly iterative efficient algorithm for linked equations) algorithm. It is found that periodic oscillation flow evolves.We propose a new convergence concept for the simulation oscillation results; the results of the numerical experiments are presented and they confirm our theoretical conclusions. The convergence result is checked in another way. It is found that the two approaches have the same results and can judge the validity of the time step. The proposed method is helpful to get reliable results efficiently.     

Environmental inversion using high-resolution matched-field processing

This paper considers the inversion of experimental field data collected with light receiving systems designed to meet operational requirements. Such operational requirements include system deployment in free drifting configurations and a limited number of acoustic receivers. A well-known consequence of a reduced spatial coverage is a poor sampling of the vertical structure of the acoustic field, leading to a severe ill-conditioning of the inverse problem and data to model cost function with a massive sidelobe structure having many local extrema. This causes difficulties to meta-heuristic global search methods, such as genetic algorithms, to converge to the true model parameters. In order to cope with this difficulty, broadband high-resolution processors are proposed for their ability to significantly attenuate sidelobes, as a contribution for improving convergence. A comparative study on simulated data shows that high-resolution methods did not outperform the conventional Bartlett processor for pinpointing the true environmental parameter when using exhaustive search. However, when a meta-heuristic technique is applied for exploring a large multidimensional search space, high-resolution methods clearly improved convergence, therefore reducing the inherent uncertainty on the final estimate. These findings are supported by the results obtained on experimental field data obtained during the Maritime Rapid Environmental Assessment 2003 sea trial.     

Hybrid bio-inspired lateral inhibition and Imperialist Competitive Algorithm for complicated image matching

Bio-inspired intelligent algorithms, such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), have been applied to solve image matching problems. However, due to high computational complexity and premature convergence problems associated with these methods, they have limitations in defining the global optimal matcher efficiently and accurately. To address these problems, we proposed a hybrid bio-inspired optimization approach, coupling the lateral inhibition mechanism and Imperialist Competitive Algorithm (ICA), to solve complicated image matching problems. With the adoption of the lateral inhibition mechanism, the global convergence of conventional ICA algorithms has been greatly improved. We demonstrate the efficiency and feasibility of the proposed approach by extensive comparative experiments.     

Accuracy preserving limiter for the high-order accurate solution of the Euler equations

Higher-order finite-volume methods have been shown to be more efficient than second-order methods. However, no consensus has been reached on how to eliminate the oscillations caused by solution discontinuities. Essentially non-oscillatory (ENO) schemes provide a solution but are computationally expensive to implement and may not converge well for steady-state problems. This work studies the extension of limiters used for second-order methods to the higher-order case. Requirements for accuracy and efficient convergence are discussed. A new limiting procedure is proposed. Ringleb’s flow problem is used to demonstrate that nearly nominal orders of accuracy for schemes up to fourth-order can be achieved in smooth regions using the new limiter. Results for the fourth-order accurate solution of transonic flow demonstrates good convergence properties and significant qualitative improvement of the solution relative the second-order method. The new limiter can also be successfully applied to reduce the dissipation of second-order schemes with minimal sacrifices in convergence properties relative to existing approaches.     

BDF-like methods for nonlinear dynamic analysis

We present several time integration algorithms of second-order accuracy that are numerically simple and effective for nonlinear elastodynamic problems. These algorithms are based on a general four-step scheme that has a resemblance to the backward differentiation formulas. We also present an extension to the composite strategy of the Bathe method. Appropriate values for the algorithmic parameters are determined based on considerations of stability and dissipativity, and less dissipative members of each algorithm have been identified. We demonstrate the convergence characteristics of the proposed algorithms with a nonlinear dynamic problem having analytic solutions, and test these algorithms with several three-dimensional nonlinear elastodynamic problems involving large deformations and rotations, employing St. Venant-Kirchhoff and compressible Neo-Hookean hyperelastic material models. These tests show that stable computations are obtained with the proposed algorithms in nonlinear situations where the trapezoidal rule encounters a well-known instability.     

改进的盲解卷积技术在远距离激光光斑图像复原中的应用

为了提高外场实验中远距离测量激光光斑位置的精度,提出利用盲解卷积技术对光斑图像进行事后复原来削弱大气湍流对光斑成像的影响。首先,介绍了经典盲解卷积算法,分析了其不足之处,并提出了一种改进的盲解卷积算法。为了提高目标函数的收敛性和收敛速度,在TV(Total Variation)目标函数加入惩罚项,并对交替迭代法进行改进。然后,用数学方法证明了改进的盲解卷积算法的收敛性。最后,进行了仿真实验。与传统算法相比,用改进算法恢复的图像信噪比至少提升了15%。文中给出了外场试验图像的实际复原效果。     

RETRACTED: A Hybrid Nonlinear Active Noise Control Method Using Chebyshev Nonlinear Filter

Investigations into active noise control (ANC) technique have been conducted with the aim of effective control of the low-frequency noise. In practice, however, the performance of currently available ANC systems degrades due to the effects of nonlinearity in the primary and secondary paths, primary noise and louder speaker. This paper proposes a hybrid control structure of nonlinear ANC system to control the non-stationary noise produced by the rotating machinery on the nonlinear primary path. A fast version of ensemble empirical mode decomposition is used to decompose the non-stationary primary noise into intrinsic mode functions, which are expanded using the second-order Chebyshev nonlinear filter and then individually controlled. The convergence of the nonlinear ANC system is also discussed. Simulation results demonstrate that proposed method outperforms the FSLMS and VFXLMS algorithms with respect to noise reduction and convergence rate.     

Preconditioning for multidimensional TOMBO imaging

In this Letter, we propose a preconditioning method to improve the convergence speed of iterative reconstruction algorithms in a compact, multidimensional, compound-eye imaging system called the thin observation module by bound optics. The condition number of the system matrix is improved by using a preconditioner matrix. To calculate the preconditioner matrix, the system model is expressed in the frequency domain. The proposed method is simulated by using a compressive sensing algorithm called the two-step iterative shrinkage/thresholding algorithm. The results showed improved reconstruction fidelity with a certain number of iterations for high signal-to-noise ratio measurements.     

一种基于恒定统计的红外图像非均匀性校正算法

对红外焦平面阵列成像系统而言,基于场景的非均匀校正技术是处理固定图案噪声的关键技术。现有的非均匀校正算法主要被收敛速度和鬼像问题所限制。提出一种新的基于恒定统计算法的自适应场景非均匀校正技术。利用红外图像序列的时域统计信息结合提出的α修正均值滤波来估计探测器的参数,通过减少样本的渐进方差估计,完成成像系统的非均匀性校正。通过模拟和真实的非均匀性图像对算法的性能进行评价。实验结果表明,在继承恒定统计算法快速收敛的同时,图像峰值信噪比较恒定校正法及常系数α校正算法分别有44.5%和32.9%的提升,图像鬼像问题有明显改善。     

基于Dual-Mode MCMA+DD双模式盲均衡算法研究

为了兼顾误差性能和收敛速度,研究了将双模修正常量模算法和判决引导算法有机结合的双模式盲均衡算法.该算法在收敛初期采用双模修正常量模算法调整均衡器,然后根据判决条件自动切换到判决引导算法,最终实现信道的盲均衡.仿真结果表明:此算法收敛速度快、稳态误差小,并能在去除码间干扰的同时纠正信道固有的相位旋转,具有很好的实用性.     

An enhanced non-uniformity correction algorithm for IRFPA based on neural network

Influenced by detector materials’ non-uniformity, growth and etching techniques, etc., every detector’s responsivity of infrared focal plane arrays (IRFPA) is different, which results in non-uniformity of IRFPA. And non-uniformity of IRFPA generates fixed pattern noises (FPN) that are superposed on infrared image. And it may degrade the infrared image quality, which greatly limits the application of IRFPA. Non-uniformity correction (NUC) is an important technique for IRFPA. The traditional non-uniformity correction algorithm based on neural network and its modified algorithms are analyzed in this paper. And a new improved non-uniformity correction algorithm based on neural network is proposed in this paper. In this algorithm, the desired image is estimated by using three successive images in an infrared sequence. And blurring effect caused by motion is avoided by applying implicit motion detection and edge detection. So the estimation image is closer to real image than the estimation image estimated by other algorithms, which results in fast convergence speed of correction parameters. A comparison is made to these algorithms in this paper. And experimental results show that the algorithm proposed in this paper can correct the non-uniformity of IRFPA effectively and it prevails over other algorithms based on neural network.