• Title/Summary/Keyword: symmetric positive definite matrix

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Numerical Stability of Cholesky Factorization in Interior Point Methods for Linear Programming (내부점 방법에서 촐레스키 분해의 수치적 안정성)

  • Seol, Tong-Ryeol;Seong, Myeong-Ki;Ahn, Jae-Geun;Park, Soon-Dal
    • Journal of Korean Institute of Industrial Engineers
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    • v.25 no.3
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    • pp.290-297
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    • 1999
  • In interior point methods for linear programming, we must solve a linear system with a symmetric positive definite matrix at every iteration, and Cholesky factorization is generally used to solve it. Therefore, if Cholesky factorization is not done successfully, many iterations are needed to find the optimal solution or we can not find it. We studied methods for improving the numerical stability of Cholesky factorization and the accuracy of the solution of the linear system.

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INTEGRABLE MODULES OVER QUANTUM GROUPS AT ROOTS OF 1

  • Cho, Young-Hyun;Kwon, Sae-Ran;Lee, In-Sok
    • Communications of the Korean Mathematical Society
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    • v.10 no.1
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    • pp.35-38
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    • 1995
  • Let A be a symmetric positive definite Cartan matrix. As in [4], we denote by U the quantum group arising from A and $U_\lambda$ be the corresponding quantum group at a root of unity $\lambda$. In [4], Lusztig constructed irreducible highest weight $U_\lambda$-modules $L_\lambda(z)$ for $z \in Z^n$ and showed that $L_\lambda(z)$ is of finite dimension over C if and only if $z \in (Z^+)^n$.

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A primal-dual log barrier algorithm of interior point methods for linear programming (선형계획을 위한 내부점법의 원문제-쌍대문제 로그장벽법)

  • 정호원
    • Korean Management Science Review
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    • v.11 no.3
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    • pp.1-11
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    • 1994
  • Recent advances in linear programming solution methodology have focused on interior point methods. This powerful new class of methods achieves significant reductions in computer time for large linear programs and solves problems significantly larger than previously possible. These methods can be examined from points of Fiacco and McCormick's barrier method, Lagrangian duality, Newton's method, and others. This study presents a primal-dual log barrier algorithm of interior point methods for linear programming. The primal-dual log barrier method is currently the most efficient and successful variant of interior point methods. This paper also addresses a Cholesky factorization method of symmetric positive definite matrices arising in interior point methods. A special structure of the matrices, called supernode, is exploited to use computational techniques such as direct addressing and loop-unrolling. Two dense matrix handling techniques are also presented to handle dense columns of the original matrix A. The two techniques may minimize storage requirement for factor matrix L and a smaller number of arithmetic operations in the matrix L computation.

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A PRECONDITIONER FOR THE NORMAL EQUATIONS

  • Salkuyeh, Davod Khojasteh
    • Journal of applied mathematics & informatics
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    • v.28 no.3_4
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    • pp.687-696
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    • 2010
  • In this paper, an algorithm for computing the sparse approximate inverse factor of matrix $A^{T}\;A$, where A is an $m\;{\times}\;n$ matrix with $m\;{\geq}\;n$ and rank(A) = n, is proposed. The computation of the inverse factor are done without computing the matrix $A^{T}\;A$. The computed sparse approximate inverse factor is applied as a preconditioner for solving normal equations in conjunction with the CGNR algorithm. Some numerical experiments on test matrices are presented to show the efficiency of the method. A comparison with some available methods is also included.

On ths Stability Issues of Linear Takagi-Sugeno Fuzzy Models

  • Joh, Joongseon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.7 no.2
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    • pp.110-121
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    • 1997
  • Stability issues of linear Takagi-Sugeno fuzzy modles are thoroughly investigated. At first, a systematic way of searching for a common symmetric positive definite P matrix (common P matrix in short), which is related to stability, is proposed for N subsystems which are under a pairwise commutativity assumption. Robustness issue under modeling uncertainty in each subsystem is then considered by proposing a quadratic stability criterion and a method of determining uncertainty bounds. Finally, it is shown that the pairwise commutative assumption can be in fact relaxed by interpreting the uncertainties as mismatch parts of non-commutative system matrices. Several examples show the validity of the proposed methods.

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Design of T-S(Takagi-Sugeno) Fuzzy Control Systems Under the Bound on the Output Energy

  • Kim, Kwang-Tae;Joh, Joog-Seon;Kwon, Woo-Hyen
    • Transactions on Control, Automation and Systems Engineering
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    • v.1 no.1
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    • pp.44-49
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    • 1999
  • This paper presents a new T-S(Tae-Sugeno) fuzzy controller design method satisfying the output energy bound. Maximum output energy via a quadratic Lyapunov function to obtain the bound on output energy is derived. LMI(Linear Matrix Inequality) problems which satisfy an output energy bound for both of the continuous-time and discrete-time T-S fuzzy control system are also derived. Solving these LMIs simultaneously, we find a common symmetric positive definite matrix P which guarantees the global asymptotic stability of the system and stable feedback gains K's satisfying the output energy bound. A simple example demonstrates validity of the proposed design method.

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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.

A PARALLEL PRECONDITIONER FOR GENERALIZED EIGENVALUE PROBLEMS BY CG-TYPE METHOD

  • MA, SANGBACK;JANG, HO-JONG
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.5 no.2
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    • pp.63-69
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    • 2001
  • In this study, we shall be concerned with computing in parallel a few of the smallest eigenvalues and their corresponding eigenvectors of the eigenvalue problem, $Ax={\lambda}Bx$, where A is symmetric, and B is symmetric positive definite. Both A and B are large and sparse. Recently iterative algorithms based on the optimization of the Rayleigh quotient have been developed, and CG scheme for the optimization of the Rayleigh quotient has been proven a very attractive and promising technique for large sparse eigenproblems for small extreme eigenvalues. As in the case of a system of linear equations, successful application of the CG scheme to eigenproblems depends also upon the preconditioning techniques. A proper choice of the preconditioner significantly improves the convergence of the CG scheme. The idea underlying the present work is a parallel computation of the Multi-Color Block SSOR preconditioning for the CG optimization of the Rayleigh quotient together with deflation techniques. Multi-Coloring is a simple technique to obatin the parallelism of order n, where n is the dimension of the matrix. Block SSOR is a symmetric preconditioner which is expected to minimize the interprocessor communication due to the blocking. We implemented the results on the CRAY-T3E with 128 nodes. The MPI(Message Passing Interface) library was adopted for the interprocessor communications. The test problems were drawn from the discretizations of partial differential equations by finite difference methods.

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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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