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本文针对求解大型稀疏非Hermitian正定线性方程组的HSS迭代方法,利用迭代法的松弛技术进行加速,提出了一种具有三个参数的超松弛HSS方法(SAHSS)和不精确的SAHSS方法(ISAHSS),它采用CG和一些Krylov子空间方法作为其内部过程,并研究了SAHSS和ISAHSS方法的收敛性.数值例子验证了新方法的有效性. 相似文献
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《应用数学与计算数学学报》2015,(3)
Golub等研究了一种带辅助预条件参数矩阵的SOR-like方法来解鞍点问题(Golub G H,Wu X,Yuan J Y.SOR-like methods for augmented systems.BIT,2001,41(1):71—85).我们用一种新的辅助预条件取法来加速该方法去解(1,1)块是对称正定M矩阵的鞍点系统,数值结果显示优于Golub等提出的预条件. 相似文献
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非Hermitian正定线性方程组的外推的HSS迭代方法 总被引:1,自引:0,他引:1
为了高效地求解大型稀疏非Hermitian正定线性方程组,在白中治、Golub和Ng提出的Hermitian和反Hermitian分裂(HSS)迭代法的基础上,通过引入新的参数并结合迭代法的松弛技术,对HSS迭代方法进行加速,提出了一种新的外推的HSS迭代方法(EHSS),并研究了该方法的收敛性.数值例子表明:通过参数值的选择,新方法比HSS方法具有更快的收敛速度和更少的迭代次数,选择了合适的参数值后,可以提高HSS方法的收敛效率. 相似文献
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对于求解大型稀疏连续Sylvester方程,Bai提出了非常有效的Hermitian和反Hermitian分裂(HSS)迭代法.为了进一步提高求解这类方程的效率,本文建立一种广义正定和反Hermitian分裂(GPSS)迭代法,并且提出不精确GPSS(IGPSS)迭代法从而可以降低计算成本.对GPSS迭代法及其不精确变体的收敛性作了详细分析.另外,建立一种超松弛加速GPSS(AGPSS)方法并且讨论了收敛性.数值结果表明了方法的高效性和鲁棒性. 相似文献
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《应用数学与计算数学学报》2015,(4)
提出了求解广义Lyapunov方程的HSS(Hermitian and skew-Hermitian splitting)迭代法,分析了该方法的收敛性,给出了收敛因子的上界.为了降低HSS迭代法的计算量,提出了求解广义Lyapunov方程的非精确HSS迭代法,并分析其收敛性.数值结果表明,求解广义Lyapunov方程的HSS迭代法及非精确HSS迭代法是有效的. 相似文献
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广义鞍点问题的松弛维数分解预条件子 总被引:1,自引:0,他引:1
本文将Benzi等提出的松弛维数分解(Relaxed dimensionalfactorization, RDF)预条件子进一步推广到广义鞍点问题上,并称为GRDF(Generalized RDF)预条件子.该预条件子可看做是用维数分裂迭代法求解广义鞍点问题而导出的改进维数分裂(Modified dimensional split, MDS)预条件子的松弛形式, 它相比MDS预条件子更接近于系数矩阵, 因而结合Krylov子空间方法(如GMRES)有更快的收敛速度.文中分析了GRDF预处理矩阵特征值的一些性质,并用数值算例验证了新预条件子的有效性. 相似文献
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非重迭型区域分解预处理共轭梯度法 总被引:4,自引:1,他引:3
本文讨论含有内部交叉点(cross point)的非重迭型区域分解预处理共轭梯度法。称一个点是交叉点,如果有三个或三个以上的子区域以该点做为共同边界点,该点为区域内点。 本文根据在对称正定块对角矩阵类中对角块是对称正定矩阵比较有效的预处理器的理论,通过简单自然的刚度矩阵分裂,基于代数方式,构造了一类预处理器并给出了预处 相似文献
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《数学的实践与认识》2015,(20)
基于分块矩阵的Schur补和Albert定理,证明了一些含有块Hadamard积的行列式不等式,并且用不同于文献的方法证明了半正定Hermitian矩阵块Hadamard积的行列式不等式的一个猜想,此结果推广了半正定Hermitian矩阵在块Hadamard积下的Oppenheim不等式. 相似文献
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For the generalized saddle-point problems with non-Hermitian (1,1) blocks, we present an HSS-based constraint preconditioner,
in which the (1,1) block of the preconditioner is constructed by the HSS method for solving the non-Hermitian positive definite
linear systems. We analyze the invertibility of the HSS-based constraint preconditioner and prove the convergence of the preconditioned
iteration method. Numerical experiments are used to demonstrate the efficiency of the preconditioner as well as the corresponding
preconditioned iteration method, especially when the (1,1) block of the saddle-point matrix is essentially non-Hermitian. 相似文献
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Ai-Li Yang 《Applied mathematics and computation》2010,216(6):1715-1722
Based on the HSS (Hermitian and skew-Hermitian splitting) and preconditioned HSS methods, we will present a generalized preconditioned HSS method for the large sparse non-Hermitian positive definite linear system. Our method is essentially a two-parameter iteration which can extend the possibility to optimize the iterative process. The iterative sequence produced by our generalized preconditioned HSS method can be proven to be convergent to the unique solution of the linear system. An exact parameter region of convergence for the method is strictly proved. A minimum value for the upper bound of the iterative spectrum is derived, which is relevant to the eigensystem of the products formed by inverse preconditioner and splitting. An efficient preconditioner based on incremental unknowns is presented for the actual implementation of the new method. The optimality and efficiency are effectively testified by some comparisons with numerical results. 相似文献
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《数学季刊》2015,(4)
Bai, Golub and Pan presented a preconditioned Hermitian and skew-Hermitian splitting(PHSS) method [Numerische Mathematik, 2004, 32: 1-32] for non-Hermitian positive semidefinite linear systems. We improve the method to solve saddle point systems whose(1,1) block is a symmetric positive definite M-matrix with a new choice of the preconditioner and compare it with other preconditioners. The results show that the new preconditioner outperforms the previous ones. 相似文献
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Zhong-zhi Bai Jun-feng Yin Yang-feng Su 《计算数学(英文版)》2006,24(4):539-552
A shift splitting concept is introduced and, correspondingly, a shift-splitting iteration scheme and a shift-splitting preconditioner are presented, for solving the large sparse system of linear equations of which the coefficient matrix is an ill-conditioned non-Hermitian positive definite matrix. The convergence property of the shift-splitting iteration method and the eigenvalue distribution of the shift-splitting preconditioned matrix are discussed in depth, and the best possible choice of the shift is investigated in detail. Numerical computations show that the shift-splitting preconditioner can induce accurate, robust and effective preconditioned Krylov subspace iteration methods for solving the large sparse non-Hermitian positive definite systems of linear equations. 相似文献
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Fast inexact subspace iteration for generalized eigenvalue problems with spectral transformation 总被引:1,自引:0,他引:1
Fei Xue 《Linear algebra and its applications》2011,435(3):601-622
We study inexact subspace iteration for solving generalized non-Hermitian eigenvalue problems with spectral transformation, with focus on a few strategies that help accelerate preconditioned iterative solution of the linear systems of equations arising in this context. We provide new insights into a special type of preconditioner with “tuning” that has been studied for this algorithm applied to standard eigenvalue problems. Specifically, we propose an alternative way to use the tuned preconditioner to achieve similar performance for generalized problems, and we show that these performance improvements can also be obtained by solving an inexpensive least squares problem. In addition, we show that the cost of iterative solution of the linear systems can be further reduced by using deflation of converged Schur vectors, special starting vectors constructed from previously solved linear systems, and iterative linear solvers with subspace recycling. The effectiveness of these techniques is demonstrated by numerical experiments. 相似文献
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We present a preconditioner for saddle point problems. The proposed preconditioner is extracted from a stationary iterative method which is convergent under a mild condition. Some properties of the preconditioner as well as the eigenvalues distribution of the preconditioned matrix are presented. The preconditioned system is solved by a Krylov subspace method like restarted GMRES. Finally, some numerical experiments on test problems arisen from finite element discretization of the Stokes problem are given to show the effectiveness of the preconditioner. 相似文献
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Recently, Cao proposed a regularized deteriorated positive and skew-Hermitian splitting (RDPSS) preconditioner for the non-Hermitian nonsingular saddle point problem. In this paper, we consider applying RDPSS preconditioner to
solve the singular saddle point problem. Moreover, we propose a two-parameter
accelerated variant of the RDPSS (ARDPSS) preconditioner to further improve its
efficiency. Theoretical analysis proves that the RDPSS and ARDPSS methods are
semi-convergent unconditionally. Some spectral properties of the corresponding preconditioned matrices are analyzed. Numerical experiments indicate that better performance can be achieved when applying the ARDPSS preconditioner to accelerate
the GMRES method for solving the singular saddle point problem. 相似文献
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For non-Hermitian saddle point linear systems, Pan, Ng and Bai presented a positive semi-definite and skew-Hermitian splitting (PSS) preconditioner (Pan et al. Appl. Math. Comput. 172, 762–771 2006), to accelerate the convergence rate of the Krylov subspace iteration methods like the GMRES method. In this paper, a relaxed positive semi-definite and skew-Hermitian (RPSS) splitting preconditioner based on the PSS preconditioner for the non-Hermitian generalized saddle point problems is considered. The distribution of eigenvalues and the form of the eigenvectors of the preconditioned matrix are analyzed. Moreover, an upper bound on the degree of the minimal polynomial is also studied. Finally, numerical experiments of a model Navier-Stokes equation are presented to illustrate the efficiency of the RPSS preconditioner compared to the PSS preconditioner, the block diagonal preconditioner (BD), and the block triangular preconditioner (BT) in terms of the number of iteration and computational time. 相似文献
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In this paper, on the basis of matrix splitting, two preconditioners are proposed and analyzed, for nonsymmetric saddle point problems. The spectral property of the preconditioned matrix is studied in detail. When the iteration parameter becomes small enough, the eigenvalues of the preconditioned matrices will gather into two clusters—one is near (0,0) and the other is near (2,0)—for the PPSS preconditioner no matter whether A is Hermitian or non-Hermitian and for the PHSS preconditioner when A is a Hermitian or real normal matrix. Numerical experiments are given, to illustrate the performances of the two preconditioners. 相似文献