A RELAXED HSS PRECONDITIONER FOR SADDLE POINT PROBLEMS FROM MESHFREE DISCRETIZATION＊

In this paper, a relaxed Hermitian and skew-Hermitian splitting （RHSS） preconditioner is proposed for saddle point problems from the element-free Galerkin （EFG） discretization method. The EFG method is one of the most widely used meshfree methods for solving partial differential equations. The RHSS preconditioner is constructed much closer to the coefficient matrix than the well-known HSS preconditioner, resulting in a RHSS fixed-point iteration. Convergence of the RHSS iteration is analyzed and an optimal parameter, which minimizes the spectral radius of the iteration matrix is described. Using the RHSS pre- conditioner to accelerate the convergence of some Krylov subspace methods （like GMRES） is also studied. Theoretical analyses show that the eigenvalues of the RHSS precondi- tioned matrix are real and located in a positive interval. Eigenvector distribution and an upper bound of the degree of the minimal polynomial of the preconditioned matrix are obtained. A practical parameter is suggested in implementing the RHSS preconditioner. Finally, some numerical experiments are illustrated to show the effectiveness of the new preconditioner.     

STABILITIES OF （A,B,C）AND NPDIRK METHODS FOR SYSTEMS OF NEUTRAL DELAY—DIFFERENTIAL EQUATIONS WITH MULTIPLE DELAYS

Consider the following neutral delay-differential equations with multiple delays (NMDDE)$$y'(t)=Ly(t)+\sum_{j=1}^{m}[M_jy(t-\tau_j)+N_jy'(t-\tau_j)],\ \ t\geq 0, (0.1)$$ where $\tau>0$, $L, M_j$ and $N_j$ are constant complex- value $d×d$ matrices. A sufficient condition for the asymptotic stability of NMDDE system (0.1) is given. The stability of Butcher's (A,B,C)-method for systems of NMDDE is studied. In addition, we present a parallel diagonally-implicit iteration RK (PDIRK) methods (NPDIRK) for systems of NMDDE, which is easier to be implemented than fully implicit RK methos. We also investigate the stability of a special class of NPDIRK methods by analyzing their stability behaviors of the solutions of (0.1).     

Skew-Hermitian Triangular Splitting Iteration Methods for Non-Hermitian Positive Definite Linear Systems of Strong Skew-Hermitian Parts

By further generalizing the skew-symmetric triangular splitting iteration method studied by Krukier, Chikina and Belokon (Applied Numerical Mathematics, 41 (2002), pp. 89–105), in this paper, we present a new iteration scheme, called the modified skew-Hermitian triangular splitting iteration method, for solving the strongly non-Hermitian systems of linear equations with positive definite coefficient matrices. We discuss the convergence property and the optimal parameters of this new method in depth. Moreover, when it is applied to precondition the Krylov subspace methods like GMRES, the preconditioning property of the modified skew-Hermitian triangular splitting iteration is analyzed in detail. Numerical results show that, as both solver and preconditioner, the modified skew-Hermitian triangular splitting iteration method is very effective for solving large sparse positive definite systems of linear equations of strong skew-Hermitian parts.     

Product-type skew-Hermitian triangular splitting iteration methods for strongly non-Hermitian positive definite linear systems

By further generalizing the modified skew-Hermitian triangular splitting iteration methods studied in [L. Wang, Z.-Z. Bai, Skew-Hermitian triangular splitting iteration methods for non-Hermitian positive definite linear systems of strong skew-Hermitian parts, BIT Numer. Math. 44 (2004) 363-386], in this paper, we present a new iteration scheme, called the product-type skew-Hermitian triangular splitting iteration method, for solving the strongly non-Hermitian systems of linear equations with positive definite coefficient matrices. We discuss the convergence property and the optimal parameters of this method. Moreover, when it is applied to precondition the Krylov subspace methods, the preconditioning property of the product-type skew-Hermitian triangular splitting iteration is analyzed in detail. Numerical results show that the product-type skew-Hermitian triangular splitting iteration method can produce high-quality preconditioners for the Krylov subspace methods for solving large sparse positive definite systems of linear equations of strong skew-Hermitian parts.     

On semi-convergence of modified HSS method for a class of complex singular linear systems

In this paper, we discuss the semi-convergence of the modified Hermitian and skew-Hermitian splitting (MHSS) iteration method for solving a broad class of complex singular linear systems. Some semi-convergence theories of the MHSS iteration method are established and are weaker than those appeared in previously published works.     

求解大规模非Hermite线性方程组的Krylov子空间型方法的收敛性分析

本文用统一的方式研究了当系数矩阵Ａ亏损且其谱位于右（左）半开平面时很多求解大规模非Ｈｅｒｍｉｔｅ线性方程组的Ｋｒｙｌｏｖ子空间型方法的收敛性，建立了有关的理论收敛界，揭示了收敛速度和Ａ的谱之间的内在联系．结果证明，当如下三种情形之一出现时，这些方法的收敛速度将会减慢：Ａ亏损，其谱的分布不理想，或Ａ的Ｊｏｒｄａｎ基病态．在证明中，我们给出了Ｃｈｅｂｙｓｈｅｖ多项式的高阶导数在复平面中某椭圆域上的若干新性质，其中之一修正了文献中广泛使用的一个结果．     

A Variant of the ORTHOMIN(2) Method for Singular Linear Systems

For singular linear systems A x=b, ORTHOMIN(2) is known theoretically to attain the minimum residual min _xR nb–A x₂ under a certain condition. However, in the actual computation with finite precision arithmetic, the residual is often observed to be reduced further than the theoretically expected level. Therefore, we propose a variant of ORTHOMIN(2), which is mathematically equivalent to the original ORTHOMIN(2) method, but uses recurrence formulas that are different from those of ORTHOMIN(2); they contain alternative expressions for the auxiliary vector and the recurrence coefficients. Although our implementation has the same computational costs as ORTHOMIN(2), numerical experiments on singular systems show that our implementation is more accurate and less affected by rounding errors than ORTHOMIN(2).     

Linear Systems Associated with Numerical Methods for Constrained Optimization

Linear systems associated with numerical methods for constrained optimization are discussed in thia paper ,It is shown that the corresponding subproblems arise in most well-known methods,no matter line search methods or trust region methods for constrained optimization can be expressed as similar systems of linear equations.All these linear systems can be viewed as some kinds of approximation to the linear system derived by the Lagrange-Newton method .Some properties of these linear systems are analyzed.     

The generalized HSS method for solving singular linear systems

For the singular, non-Hermitian, and positive semidefinite linear systems, we propose an alternating-direction iterative method with two parameters based on the Hermitian and skew-Hermitian splitting. The semi-convergence analysis and the quasi-optimal parameters of the proposed method are discussed. Moreover, the corresponding preconditioner based on the splitting is given to improve the semi-convergence rate of the GMRES method. Numerical examples are given to illustrate the theoretical results and the efficiency of the generalized HSS method either as a solver or a preconditioner for GMRES.     

关于结构型单调变分不等式的平行分裂增广Lagrangian方法的O(1/t)阶收敛性(英文)

最近,何[3]证明了投影收缩算法的O(1/t)阶收敛性.受此启发,本文证明了结构型单调变分不等式的平行分裂增广Lagrangian方法的O(1/t)阶收敛性.     

On IOM(q): The Incomplete Orthogonalization Method for Large Unsymmetric Linear Systems

The incomplete orthogonalization method (IOM(q)), a truncated version of the full orthogonalization method (FOM) proposed by Saad, has been used for solving large unsymmetric linear systems. However, no convergence analysis has been given. In this paper, IOM(q) is analysed in detail from a theoretical point of view. A number of important results are derived showing how the departure of the matrix A from symmetric affects the basis vectors generated by IOM(q), and some relationships between the residuals for IOM(q) and FOM are established. The results show that IOM(q) behaves much like FOM once the basis vectors generated by it are well conditioned. However, it is proved that IOM(q) may generate an ill-conditioned basis for a general unsymmetric matrix such that IOM(q) may fail to converge or at least cannot behave like FOM. Owing to the mathematical equivalence between IOM(q) and the truncated ORTHORES(q) developed by Young and Jea, insights are given into the convergence of the latter. A possible strategy is proposed for choosing the parameter q involved in IOM(q). Numerical experiments are reported to show convergence behaviour of IOM(q) and of its restarted version.