Regularization of Singularities in the Weighted Summation of Dirac-Delta Functions for the Spectral Solution of Hyperbolic Conservation Laws

Singular source terms expressed as weighted summations of Dirac-delta functions are regularized through approximation theory with convolution operators. We consider the numerical solution of scalar and one-dimensional hyperbolic conservation laws with the singular source by spectral Chebyshev collocation methods. The regularization is obtained by convolution with a high-order compactly supported Dirac-delta approximation whose overall accuracy is controlled by the number of vanishing moments, degree of smoothness and length of the support (scaling parameter). An optimal scaling parameter that leads to a high-order accurate representation of the singular source at smooth parts and full convergence order away from the singularities in the spectral solution is derived. The accuracy of the regularization and the spectral solution is assessed by solving an advection and Burgers equation with smooth initial data. Numerical results illustrate the enhanced accuracy of the spectral method through the proposed regularization.     

电容层析成像系统图像重建算法的研究

本文利用Tikhonov正则化和奇异系统理论,分析了引起电容层析成像系统逆问题不适定性的根本原因是由于敏感场矩阵小奇异值的存在。针对一般Tikhonov正则化方法将所有的奇异值都采取同一正则化参数修正带来的误差,本文将小奇异值对应的项设定正则化参数,而舍去零奇异值对应向量,既减少了误差又加快了速度。例算结果表明,用本文方法重建图像,比其它如线性反投影算法(LBP)、Landweber迭代法及一般Tikhonov正则化算法,都有一定程度的改善。     

Numerical solution of singular ODE eigenvalue problems in electronic structure computations

We put forward a new method for the solution of eigenvalue problems for (systems of) ordinary differential equations, where our main focus is on eigenvalue problems for singular Schrödinger equations arising for example in electronic structure computations. In most established standard methods, the generation of the starting values for the computation of eigenvalues of higher index is a critical issue. Our approach comprises two stages: First we generate rough approximations by a matrix method, which yields several eigenvalues and associated eigenfunctions simultaneously, albeit with moderate accuracy. In a second stage, these approximations are used as starting values for a collocation method which yields approximations of high accuracy efficiently due to an adaptive mesh selection strategy, and additionally provides reliable error estimates. We successfully apply our method to the solution of the quantum mechanical Kepler, Yukawa and the coupled ODE Stark problems.     

Determining singular solutions of polynomial systems via symbolic-numeric reduction to geometric involutive forms

We present a method based on symbolic-numeric reduction to geometric involutive form to compute the primary component of and a basis of Max Noether space for a polynomial system at an isolated singular solution. The singular solution can be known exactly or approximately. For the case where the singular solution is known with limited accuracy, we then propose a generalized quadratic Newton iteration for refining it to high accuracy.     

基于二次奇异值分解和最小二乘支持向量机的轴承故障诊断方法

为了解决奇异值分解(SVD)对不同信号分解的有效奇异值个数不同,而影响故障识别准确性的难题,提出了基于二次SVD和最小二乘支持向量机(LS-SVM)的故障诊断方法。该方法利用奇异值曲率谱自适应选择有效奇异值重构信号,进行二次SVD处理,获得相同个数的正交分量,求解其能量熵,并构造故障特征向量,用于LS-SVM分类模型故障识别。将该方法应用于轴承故障诊断,与利用特定个数的主奇异值作为特征向量的方法相比,准确度提高了13.34%,表明了该方法的可行性和有效性。     

Numerical performance of hyperplane constrained method and its hybrid method for singular value decomposition

The hyperplane constrained method has been proposed in Yadani et al. (Appl Math Comp 216:779–790, 2010) computing singular value decomposition (SVD) of matrix. In the method, the SVD is replaced with solving nonlinear systems whose solutions are constrained on hyperplane, and then their solutions are computed with the help of Newton’s iterative method. In this paper, we present a new convergence theorem concerning the hyperplane constrained method in finite arithmetic. We also clarify the numerical performance of the hyperplane constrained method. In numerical experiments, we first show that the computed singular values and singular vectors are with high accuracy, even if the target matrix of SVD has small singular values, almost the same singular values, not small condition number. Though the hyperplane constrained method requires not small amount of computations, it fastens by combining other fast singular value decomposition method. We next propose a hybrid method which adopts the singular vectors computed by other fast method as the initial guess of the Newton type iteration in order to decrease the iteration number. By numerical experiments, we can see that the hybrid method runs faster than the original hyperplane constrained method with almost same accuracy.     

The calculation of singular coefficients

We consider in this paper the calculation of the ‘singular coefficients’ associated with the solution of an elliptic partial differential equation near a singular point; a re-entrant corner, or a crack tip, etc. These are the coefficients in the relevant singular expansion of the solution near the point of singularity; they often have physical relevance, and it is of interest to be able to calculate them accurately. We consider the problem in the context of the global element method; this is a variable-order finite element method designed to be capable of producing highly accurate solutions for singular problems, even in the neighbourhood of the singularity. If the values of the singular coefficients are needed, these must be extracted from the computed solution; we show in this paper that a suitably defined least-squares fitting procedure allows the calculation of values for the leading singular coefficients which are as accurate as the underlying solution.     

虚拟阵列Khatri-Rao积与子空间联合稀疏表示的DOA估计方法

利用目标信号在空域分布的稀疏性,该文提出了一种基于虚拟阵列Khatri-Rao(KR)积与信号子空间联合稀疏表示的单快拍DOA估计方法;该方法利用单次快拍的采样数据,构造出双向虚拟阵列数据,并对虚拟阵列数据的协方差矩阵进行KR积变换处理,然后对向量化后的数据进行顺序重构,利用重构矩阵的大奇异值对应的左奇异向量为估计信号子空间;最后,利用凸优化工具箱对稀疏模型进行二阶凸规划的优化求解,得到高精度的DOA估计值;仿真实验验证了算法的有效性,在低信噪比下比传统MUSIC和OMP算法具有更高的估计精度。     

A parameter uniform B-spline collocation method for solving singularly perturbed turning point problem having twin boundary layers

A numerical scheme is proposed to solve singularly perturbed two-point boundary value problems with a turning point exhibiting twin boundary layers. The scheme comprises B-spline collocation method on a non-uniform mesh of Shishkin type. Asymptotic bounds are established for the derivative of the analytical solution of a turning point problem. The present method is boundary layer resolving as well as second-order accurate in the maximum norm. A brief analysis has been carried out to prove the uniform convergence with respect to the singular perturbation parameter ? by decomposing the solution into smooth and singular components. Some relevant numerical examples are also illustrated to verify computationally the theoretical aspects.     

Boundary element method based on preliminary discretization

A new numerical method for solving wave diffraction problems is given. The method is based on the concept of boundary elements; i.e., the unknown values are the field values on the surface of the scatterer. An analog of a boundary element method rather than a numerical approximation of the initial (continuous) problem is constructed for an approximate statement of the problem on the discrete lattice. Although it reduces the accuracy of the method, it helps to simplify the implementation significantly since the Green functions of the problem are no longer singular. In order to ensure the solution to the diffraction problem is unique (i.e., to suppress fictitious resonances), a new method is constructed similarly to the CFIE approach developed for the classical boundary element method.     

Application of Vasileva's singular perturbation method to a problem in ecology

The simultaneous presence of fast and slow processes in ecological models leads to the formulation of model equations in a form amenable for the analysis by singular perturbation method. The method as originally proposed by Vasileva (1963) is applied to a specific species-resource logistic model and an algorithm useful for implementation on a digital computer is given. The solutions are obtained for zeroth, first and second order approximations. The accuracy of the solutions is examined by considering the integral-squared-error between the exact solutions and the perturbed solutions. The variation of this error with respect to the small parameter associated with the perturbation method is studied. An important result due to Tikhnov (1950) in the singular perturbation theory is illustrated. It is seen that Vasileva's singular perturbation method is a powerful analytical tool for investigations of various phenomena in the natural sciences.     

A symbolic-numerical algorithm for the computation of matrix elements in the parametric eigenvalue problem

A symbolic-numerical algorithm for the computation of the matrix elements in the parametric eigenvalue problem to a prescribed accuracy is presented. A procedure for calculating the oblate angular spheroidal functions that depend on a parameter is discussed. This procedure also yields the corresponding eigenvalues and the matrix elements (integrals of the eigenfunctions multiplied by their derivatives with respect to the parameter). The efficiency of the algorithm is confirmed by the computation of the eigenvalues, eigenfunctions, and the matrix elements and by the comparison with the known data and the asymptotic expansions for small and large values of the parameter. The algorithm is implemented as a package of programs in Maple-Fortran and is used for the reduction of a singular two-dimensional boundary value problem for the elliptic second-order partial differential equation to a regular boundary value problem for a system of second-order ordinary differential equations using the Kantorovich method.     

基于细化图像宏观弧线特征的指纹分类算法*

针对活体指纹采集样本提出了一种新的基于细化图像的指纹分类算法,定义并通过采用脊线追踪算法成功提取了一种反映指纹纹线变化特点和规律的新参量,即宏观弧线特征向量。利用这一新特征对FVC2004库中的指纹进行分类,准确率达98.9%以上,并且对低质量指纹图像具有良好的鲁棒性,消除了传统指纹分类算法过分依赖奇异点的缺陷,具有很强的实用性和一定的推广价值。     

B-spline method for solving Bratu's problem

In this paper, we propose a B-spline method for solving the one-dimensional Bratu's problem. The numerical approximations to the exact solution are computed and then compared with other existing methods. The effectiveness and accuracy of the B-spline method is verified for different values of the parameter, below its critical value, where two solutions occur.     

On applications of singular perturbation techniques in nonlinear optimal control

The technique of singular perturbations (SPT) has been applied with considerable success in several nonlinear optimal control problems. In many cases the zero-order approximation of the optimal control function has been expressed in a feedback form. This paper deals with topics involved in such closed-loop application, which seem to merit further discussion. It is formally demonstrated that a ‘forced’ singular perturbation model (obtained by artificial insertion of the perturbation parameter) results in the same zero-order composite feedback control solution as a classical singularly perturbed model (where a small parameter of physical significance appears as a consequence of a scaling transformation). The accuracy of the zero-order feedback approximation depends in both cases on the actual time scale separation of the variables. Two inherent limitations of the feedback solution are also pointed out: (1) first and higher-order correction terms of the zero-order approximation have to be computed by a predictive or off-line integration; (2) on-line implementation of SPT control strategy in a terminal boundary layer requires iterative computations. A simple pursuit problem serves as an illustrative example.     

广义分布参数系统的初值问题

本文定义了广义左逆、广义Ｆｏｕｒｉｅｒ变换，矩产方根等概念，论述了由带奇异系数矩耦合偏微分方程描述的广义分布参数系统，由广义Ｆｕｒｉｅｒ变换定理讨论了广义分布参数系统的初值问题，得到了该系统的解及其相容的初值条件。     

A truncated Levenberg-Marquardt algorithm for the calibration of highly parameterized nonlinear models

We propose a modification to the Levenberg-Marquardt minimization algorithm for a more robust and more efficient calibration of highly parameterized, strongly nonlinear models of multiphase flow through porous media. The new method combines the advantages of truncated singular value decomposition with those of the classical Levenberg-Marquardt algorithm, thus enabling a more robust solution of underdetermined inverse problems with complex relations between the parameters to be estimated and the observable state variables used for calibration. The truncation limit separating the solution space from the calibration null space is re-evaluated during the iterative calibration process. In between these re-evaluations, fewer forward simulations are required, compared to the standard approach, to calculate the approximate sensitivity matrix. Truncated singular values are used to calculate the Levenberg-Marquardt parameter updates, ensuring that safe small steps along the steepest-descent direction are taken for highly correlated parameters of low sensitivity, whereas efficient quasi-Gauss-Newton steps are taken for independent parameters with high impact. The performance of the proposed scheme is demonstrated for a synthetic data set representing infiltration into a partially saturated, heterogeneous soil, where hydrogeological, petrophysical, and geostatistical parameters are estimated based on the joint inversion of hydrological and geophysical data.     

A new parameter estimate in singular perturbations

A new upper bound is obtained for the singular perturbation parameter of an asymptotically stable singularly perturbed system. General time-invariant systems with a single small parameter are considered. The paper employs a Riccati equation whose solution is known to facilitate the exact decoupling of fast and slow dynamics. An application of the Brouwer fixed point theorem to the Riccati equation and of Liapunov's direct method to the fast and slow subsystems results in the desired upper bound. Computation of the estimate requires only the solution of two Liapunov matrix equations.     

Constrained feedback control of imperfectly known singularly perturbed non-linear systems

Global attractors are investigated for a class of imperfectly known, singularly perturbed, dynamic control systems. The uncertain systems are modelled as non-linear perturbations to a known non-linear idealized system and are represented by two time-scale subsystems. The two subsystems, which depend on a scalar singular perturbation parameter, represent a singularly perturbed system which has the property that the system reduces to one of lower order when the singular perturbation parameter is set to zero. It is assumed that the full-order system is subject to constraints on the control inputs. A class of constrained feedback controllers is developed which assures global uniform attraction of a compact set, containing the state origin, for all values of the singular perturbation parameter less than some threshold value.     

Eigenvalue-eigenvector sensitivity analysis of linear time-invariant singular systems

This note refers to the eigenvalue-eigenvector sensitivity analysis of linear time-invariant multivariable singular systems. Procedures that can be easily programmed on a digital computer are presented for the determination of the deviation of the eigenvalues and the corresponding right and left eigenvectors which are caused by the system's parameter changes about their nominal values. The method is illustrated by two examples.