• Journal of applied mathematics & informatics
• /
• v.8 no.2
• /
• pp.305-326
• /
• 2001

We introduce a class of multilevel recursive incomplete LU preconditioning techniques (RILUM) for solving general sparse matrices. This techniques is based on a recursive two by two block incomplete LU factorization on the coefficient martix. The coarse level system is constructed as an (approximate) Schur complement. A dynamic preconditioner is obtained by solving the Schur complement matrix approximately. The novelty of the proposed techniques is to solve the Schur complement matrix by a preconditioned Krylov subspace method. Such a reduction process is repeated to yield a multilevel recursive preconditioner.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.525-525
• /
• 2000

In this paper, we present recursive algorithms for state space model identification using subspace extraction via Schur complement. It is shown that an estimate of the extended observability matrix can be obtained by subspace extraction via Schur complement. A relationship between the least squares residual and the Schur complement matrix obtained from input-output data is shown, and the recursive algorithms for the subspace-based state-space model identification (4SID) methods are developed. We also proposed the above algorithm for an instrumental variable (IV) based 4SID method. Finally, a numerical example of the application of the algorithms is illustrated.

• Structural Engineering and Mechanics
• /
• v.30 no.4
• /
• pp.467-480
• /
• 2008

An aggregation multigrid method (AMM) is a leading iterative solver in solid mechanics. Recently, AMM is applied for solving Schur Complement system in the FE analysis of shell structures. In this work, an extended application of AMM for solving Schur Complement system in the FE analysis of continuum elements is presented. Further, the performance of the proposed AMM in multiple load cases, which is a challenging problem for an iterative solver, is studied. The proposed method is developed by combining the substructuring and the multigrid methods. The substructuring method avoids factorizing the full-size matrix of an original system and the multigrid method gives near-optimal convergence. This method is demonstrated for the FE analysis of several elastostatic problems. The numerical results show better performance by the proposed method as compared to the preconditioned conjugate gradient method. The smaller computational cost for the iterative procedure of the proposed method gives a good alternative to a direct solver in large systems with multiple load cases.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1998.10a
• /
• pp.67-70
• /
• 1998

The computational speed of interior point method of linear programming depends on the speed of Cholesky factorization to solve AΘA$^{T}$ $\Delta$y=b. If the coefficient matrix A has dense columns then the matrix AΘA$^{T}$ becomes a dense matrix. This causes Cholesky factorization to be slow. The Schur complement method is applied to treat dense columns in many implementations but suffers from its numerical unstability. We study efficient implementation of Schur complement method. We achieve improvements in computational speed and numerical stability.rical stability.

• Journal of applied mathematics & informatics
• /
• v.33 no.3_4
• /
• pp.247-260
• /
• 2015

The special form of Schur complement is extended to have a Schur's formula to obtains the explicit formula of determinant, inverse, and eigenvector formula of the doubly Leslie matrix which is the generalized forms of the Leslie matrix. It is also a generalized form of the doubly companion matrix, and the companion matrix, respectively. The doubly Leslie matrix is a nonderogatory matrix.

• Journal of applied mathematics & informatics
• /
• v.25 no.1_2
• /
• pp.415-424
• /
• 2007

The generalized inverses have many important applications in the aspects of theoretic research and numerical computations and therefore they were studied by many authors. In this paper we get some necessary and sufficient conditions of the forward order law for {1}-inverse of multiple matrices products $A\;=\;A_1A_2{\cdots}A_n$ by using the maximal rank of generalized Schur complement.

• Journal of applied mathematics & informatics
• /
• v.31 no.3_4
• /
• pp.343-352
• /
• 2013

In this paper, we give a formula of $(P+Q)^D$ under the conditions $P^2Q+QPQ=0$ and $P^3Q=0$. Then applying it to give some results of block matrix $M=(^A_C^B_D)$ (A and D are square matrices) with generalized Schur complement is zero under some conditions. Finally, numerical examples are given to illustrate our results.

• Honam Mathematical Journal
• /
• v.40 no.1
• /
• pp.155-162
• /
• 2018

In this paper, we are concerned with hyponormal Toeplitz operators on the Hardy space of the unit circle. Our main result of this paper is to provide a simple and transparent proof on the hyponormality of Toeplitz operators with symmetric-type symbols via Schur complement lemma.

• Journal of applied mathematics & informatics
• /
• v.28 no.3_4
• /
• pp.987-992
• /
• 2010

H-matrix is a special class of matrices with wide applications in engineering and scientific computation, how to judge if a given matrix is an H-matrix is very important, especially for large scale matrices. In this paper, we obtain several new practical criteria for judging nonsingular H-matrices by using the partitioning technique and Schur complement of matrices. Their effectiveness is illustrated by numerical examples.

• Journal of applied mathematics & informatics
• /
• v.18 no.1_2
• /
• pp.321-328
• /
• 2005

We investigate a matrix inequality on Schur complements defined by {1}-generalized inverses, and obtain simultaneously a necessary and sufficient condition under which the inequality turns into an equality. This extends two existing matrix inequalities on Schur complements defined respectively by inverses and Moore-Penrose generalized inverses (see Wang et al. [Lin. Alg. Appl., 302-303(1999)163-172] and Liu and Wang [Lin. Alg. Appl., 293(1999)233-241]). Moreover, the non-uniqueness of $\{1\}$-generalized inverses yields the complicatedness of the extension.