• Title/Summary/Keyword: symmetric positive definite

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A MULTILEVEL BLOCK INCOMPLETE CHOLESKY PRECONDITIONER FOR SOLVING NORMAL EQUATIONS IN LINEAR LEAST SQUARES PROBLEMS

  • Jun, Zhang;Tong, Xiao
    • Journal of applied mathematics & informatics
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    • v.11 no.1_2
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    • pp.59-80
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    • 2003
  • An incomplete factorization method for preconditioning symmetric positive definite matrices is introduced to solve normal equations. The normal equations are form to solve linear least squares problems. The procedure is based on a block incomplete Cholesky factorization and a multilevel recursive strategy with an approximate Schur complement matrix formed implicitly. A diagonal perturbation strategy is implemented to enhance factorization robustness. The factors obtained are used as a preconditioner for the conjugate gradient method. Numerical experiments are used to show the robustness and efficiency of this preconditioning technique, and to compare it with two other preconditioners.

A New Ordering Method Using Elimination Trees (삭제나무를 이용한 새로운 순서화 방법)

  • Park, Chan-Kyoo;Doh, Seung-yong;Park, Soon-dal
    • Journal of Korean Institute of Industrial Engineers
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    • v.29 no.1
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    • pp.78-89
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    • 2003
  • Ordering is performed to reduce the amount of fill-ins of the Cholesky factor of a symmetric positive definite matrix. This paper proposes a new ordering algorithm that reduces the fill-ins of the Cholesky factor iteratively by elimination tree rotations and clique separators. Elimination tree rotations have been used mainly to reorder the rows of the permuted matrix for the efficiency of storage space management or parallel processing, etc. In the proposed algorithm, however, they are repeatedly performed to reduce the fill-ins of the Cholesky factor. In addition, we presents a simple method for finding a minimal node separator between arbitrary two nodes of a chordal graph. The proposed reordering procedure using clique separators enables us to obtain another order of rows of which the number of till-ins decreases strictly.

ANALYSIS AND COMPUTATIONS OF LEAST-SQUARES METHOD FOR OPTIMAL CONTROL PROBLEMS FOR THE STOKES EQUATIONS

  • Choi, Young-Mi;Kim, Sang-Dong;Lee, Hyung-Chun
    • Journal of the Korean Mathematical Society
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    • v.46 no.5
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    • pp.1007-1025
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    • 2009
  • First-order least-squares method of a distributed optimal control problem for the incompressible Stokes equations is considered. An optimality system for the optimal solution are reformulated to the equivalent first-order system by introducing the vorticity and then the least-squares functional corresponding to the system is defined in terms of the sum of the squared $H^{-1}$ and $L^2$ norms of the residual equations of the system. Finite element approximations are studied and optimal error estimates are obtained. Resulting linear system of the optimality system is symmetric and positive definite. The V-cycle multigrid method is applied to the system to test computational efficiency.

GLOBAL WEAK MORREY ESTIMATES FOR SOME ULTRAPARABOLIC OPERATORS OF KOLMOGOROV-FOKKER-PLANCK TYPE

  • Feng, Xiaojing;Niu, Pengcheng;Zhu, Maochun
    • Bulletin of the Korean Mathematical Society
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    • v.51 no.5
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    • pp.1241-1257
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    • 2014
  • We consider a class of hypoelliptic operators of the following type $$L=\sum_{i,j=1}^{p_0}a_{ij}{\partial}^2_{x_ix_j}+\sum_{i,j=1}^{N}b_{ij}x_i{\partial}_{x_j}-{\partial}_t$$, where ($a_{ij}$), ($b_{ij}$) are constant matrices and ($a_{ij}$) is symmetric positive definite on $\mathbb{R}^{p_0}$ ($p_0{\leqslant}N$). By establishing global Morrey estimates of singular integral on the homogenous space and the relation between Morrey space and weak Morrey space, we obtain the global weak Morrey estimates of the operator L on the whole space $\mathbb{R}^{N+1}$.

A New Design Method for T-S Fuzzy Controller with Pole Placement Constraints

  • Joh, Joongseon;Jeung, Eun-Tae;Chung, Won-Jee;Kwon, Sung-Ha
    • Journal of the Korean Institute of Intelligent Systems
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    • v.7 no.3
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    • pp.72-80
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    • 1997
  • A new design method for Takagi-Sugeno (T-S in short) fuzzy controller which guarantees global asymptotic stability and satisfies a desired performance is proposed in this paper. The method uses LMI(Linear Matrix Inequality) approach to find the common symmetric positive definite matrix P and feedback fains K/sub i/, i= 1, 2,..., r, numerically. The LMIs for stability criterion which treats P and K'/sub i/s as matrix variables is derived from Wang et al.'s stability criterion. Wang et al.'s stability criterion is nonlinear MIs since P and K'/sub i/s are coupled together. The desired performance is represented as $ LMIs which place the closed-loop poles of $ local subsystems within the desired region in s-plane. By solving the stability LMIs and pole placement constraint LMIs simultaneously, the feedback gains K'/sub i/s which gurarntee global asymptotic stability and satisfy the desired performance are determined. The design method is verified by designing a T-S fuzzy controller for an inverted pendulum with a cart using the proposed method.

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Parallel Algorithm of Conjugate Gradient Solver using OpenGL Compute Shader

  • Va, Hongly;Lee, Do-keyong;Hong, Min
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.1
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    • pp.1-9
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    • 2021
  • OpenGL compute shader is a shader stage that operate differently from other shader stage and it can be used for the calculating purpose of any data in parallel. This paper proposes a GPU-based parallel algorithm for computing sparse linear systems through conjugate gradient using an iterative method, which perform calculation on OpenGL compute shader. Basically, this sparse linear solver is used to solve large linear systems such as symmetric positive definite matrix. Four well-known matrix formats (Dense, COO, ELL and CSR) have been used for matrix storage. The performance comparison from our experimental tests using eight sparse matrices shows that GPU-based linear solving system much faster than CPU-based linear solving system with the best average computing time 0.64ms in GPU-based and 15.37ms in CPU-based.

A study on the multifrontal method in interior point method (내부점 선형계획법에서의 멀티프런탈방법에 관한 연구)

  • 김병규;박순달
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1995.09a
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    • pp.370-380
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    • 1995
  • 선형계획법의 해법으로 최근에는 내부점기법(Interior Point Method)가 관심 을 끌고 있다. 이 내부점 기법은 계산복잡도 뿐만 아니라 수행속도면에서도 우수한 결과를 보이고 있다. 이 방법은 매 회 대칭양정치(Symmetric Positive Definite)인 선형시스템을 풀어야 하는데 이 과정이 전체 내부점 수 행시간의 80-90%를 차지한다. 따라서 내부점 기법의 수행속도는 대칭양정치 인 선형시스템을 효율적으로 푸는 방법에 달려 있다. 대칭양정치인 선형시스 템을 풀기 위해서는 상하분해를 이용하게 되는 데 가우스소거를 이용해서 상하 분해를 하는 경우 매 단계에서 행렬의 모든 요소를 가지고 있을 필요 가 없다. 행렬의 모든 요소에 대한 정보를 동시에 필요로 하지 않는다. 즉, 현 단계에서 가우스소거와 관련된 열들에 대한 정보만 있으면 상하 분해가 가능하고 이러한 개념을 이용한 방법이 프런탈방법이다. 프런탈 방법은 대형 선형계획 문제를 풀기에 유리하다는 장점이 있다. 이러한 프런탈 방법을 확 장해서 동시에 여러 개의 프런탈을 계산하는 방법이 멀티프런탈방법이다. 이 방법은 알고리듬 자체가 병렬처리에 적합하기 때문에 병렬처리와 관련해서 도 많은 연구가 수행되고 있다. 본 연구에서는 삭제나무(Elimination Tree)를 이용한 프런탈 방법과 프런탈방법에 슈퍼노드의 개념을 도입한 슈퍼노들 프 런탈방법등에 대해서 이제까지의 연구 현황을 알아보고 프런탈방법에 적합 하고 효율적인 자료 구조와 멀티프런탈 방법에 적용 가능한 병렬알고리듬에 대하여 연구하고자 한다. 본 연구결과 기대효과로는 프런탈 방법에 적합하고 효율적인 자료 구조와 멀티프런탈 방법에 적용 가능한 병렬알고리듬을 개발 함으로써 내부점 선형계획법의 수행속도의 개선에 도움이 될 것이다.성요소들을 제시하였다.용자 만족도가 보다 높은 것으 로 나타났다. 할 수 있는 효율적인 distributed system를 개발하는 것을 제시하였다. 본 논문은 데이타베이스론의 입장에서 아직 정립되어 있지 않은 분산 환경하에서의 관계형 데이타베이스의 데이타관리의 분류체계를 나름대로 정립하였다는데 그 의의가 있다. 또한 이것의 응용은 현재 분산데이타베이스 구축에 있어 나타나는 기술적인 문제점들을 어느정도 보완할 수 있다는 점에서 그 중요성이 있다.ence of a small(IxEpc),hot(Tex> SOK) core which contains two tempegatlue peaks at -15" east and north of MDS. The column density of HCaN is (1-3):n1014cm-2. Column density at distant position from MD5 is larger than that in the (:entral region. We have deduced that this hot-core has a mass of 10sR1 which i:s about an order of magnitude larger those obtained by previous studies.previous studies.업순서들의 상관관계를 고려하여 보다 개선된 해를 구하기 위한 연구가 요구된다. 또한, 준비작업비용을 발생시키는 작업장의 작업순서결정에 대해서도 연구를 행하여, 보완작업비용과 준비비용을 고려한 GMMAL 작업순서문제를 해결하기 위한 연구가 수행되어야 할 것이다.로 이루어 져야 할 것이다.태를 보다 효율적으로 증진시킬 수 있는 대안이 마련되어져야 한다고 사료된다.$\ulcorner$순응$\lrcorner$<

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