The Experts below are selected from a list of 231 Experts worldwide ranked by ideXlab platform

Fujio Kako - One of the best experts on this subject based on the ideXlab platform.

  • Solving Parametric Sparse Linear Systems by Local Blocking
    ACM Communications in Computer Algebra, 2015
    Co-Authors: Tateaki Sasaki, Daiju Inaba, Fujio Kako
    Abstract:

    In solving parametric sparse linear systems, we want 1) to know relations on parametric coefficients which change the system largely, 2) to express the parametric solution in a Concise Form suitable for theoretical and numerical analysis, and 3) to find simplified systems which show characteristic features of the system. The block triangularization is a standard technique in solving the sparse linear systems. In this paper, we attack the above problems by introducing a concept of local blocks. The conventional block corresponds to a strongly connected maximal subgraph of the associated directed graph for the coefficient matrix, and our local blocks correspond to strongly connected non-maximal subgraphs. By determining local blocks in a nested way and solving subsystems from low to higher ones, we replace sub-expressions by solver parameters systematically, obtaining the solution in a Concise Form. Furthermore, we show an idea to Form simple systems which show characteristic features of the whole system.

  • CASC - Solving Parametric Sparse Linear Systems by Local Blocking
    Computer Algebra in Scientific Computing, 2014
    Co-Authors: Tateaki Sasaki, Daiju Inaba, Fujio Kako
    Abstract:

    In solving parametric sparse linear systems, we want 1) to know relations on parametric coefficients which change the system largely, 2) to express the parametric solution in a Concise Form suitable for theoretical and numerical analysis, and 3) to find simplified systems which show characteristic features of the system. The block triangularization is a standard technique in solving the sparse linear systems. In this paper, we attack the above problems by introducing a concept of local blocks. The conventional block corresponds to a strongly connected maximal subgraph of the associated directed graph for the coefficient matrix, and our local blocks correspond to strongly connected non-maximal subgraphs. By determining local blocks in a nested way and solving subsystems from low to higher ones, we replace sub-expressions by solver parameters systematically, obtaining the solution in a Concise Form. Furthermore, we show an idea to Form simple systems which show characteristic features of the whole system.

Tateaki Sasaki - One of the best experts on this subject based on the ideXlab platform.

  • Solving Parametric Sparse Linear Systems by Local Blocking
    ACM Communications in Computer Algebra, 2015
    Co-Authors: Tateaki Sasaki, Daiju Inaba, Fujio Kako
    Abstract:

    In solving parametric sparse linear systems, we want 1) to know relations on parametric coefficients which change the system largely, 2) to express the parametric solution in a Concise Form suitable for theoretical and numerical analysis, and 3) to find simplified systems which show characteristic features of the system. The block triangularization is a standard technique in solving the sparse linear systems. In this paper, we attack the above problems by introducing a concept of local blocks. The conventional block corresponds to a strongly connected maximal subgraph of the associated directed graph for the coefficient matrix, and our local blocks correspond to strongly connected non-maximal subgraphs. By determining local blocks in a nested way and solving subsystems from low to higher ones, we replace sub-expressions by solver parameters systematically, obtaining the solution in a Concise Form. Furthermore, we show an idea to Form simple systems which show characteristic features of the whole system.

  • CASC - Solving Parametric Sparse Linear Systems by Local Blocking
    Computer Algebra in Scientific Computing, 2014
    Co-Authors: Tateaki Sasaki, Daiju Inaba, Fujio Kako
    Abstract:

    In solving parametric sparse linear systems, we want 1) to know relations on parametric coefficients which change the system largely, 2) to express the parametric solution in a Concise Form suitable for theoretical and numerical analysis, and 3) to find simplified systems which show characteristic features of the system. The block triangularization is a standard technique in solving the sparse linear systems. In this paper, we attack the above problems by introducing a concept of local blocks. The conventional block corresponds to a strongly connected maximal subgraph of the associated directed graph for the coefficient matrix, and our local blocks correspond to strongly connected non-maximal subgraphs. By determining local blocks in a nested way and solving subsystems from low to higher ones, we replace sub-expressions by solver parameters systematically, obtaining the solution in a Concise Form. Furthermore, we show an idea to Form simple systems which show characteristic features of the whole system.

Robert Demolombe - One of the best experts on this subject based on the ideXlab platform.

  • FQAS - Abstract Objects to Represent Large Answers to Queries in a Concise Form
    Flexible Query Answering Systems, 2020
    Co-Authors: Robert Demolombe
    Abstract:

    Abstract objects can be used to represent in a Concise Form answers that are communicated by telephone. We present a Formal framework in first order logic in which are defined abtract answers, their lower bounds and their upper bounds. Algebraic Formulas are given to efficiently compute the abstract answers from the abstraction of the predicates that occur in a given query. We also present a method to reduce the error caused by the abstraction process that has to be computed when users want to get an exact answer.

  • abstract objects to represent large answers to queries in a Concise Form
    Flexible Query Answering Systems, 2001
    Co-Authors: Robert Demolombe
    Abstract:

    Abstract objects can be used to represent in a Concise Form answers that are communicated by telephone. We present a Formal framework in first order logic in which are defined abtract answers, their lower bounds and their upper bounds. Algebraic Formulas are given to efficiently compute the abstract answers from the abstraction of the predicates that occur in a given query. We also present a method to reduce the error caused by the abstraction process that has to be computed when users want to get an exact answer.

Evgeny A. Ryabov - One of the best experts on this subject based on the ideXlab platform.

Daiju Inaba - One of the best experts on this subject based on the ideXlab platform.

  • Solving Parametric Sparse Linear Systems by Local Blocking
    ACM Communications in Computer Algebra, 2015
    Co-Authors: Tateaki Sasaki, Daiju Inaba, Fujio Kako
    Abstract:

    In solving parametric sparse linear systems, we want 1) to know relations on parametric coefficients which change the system largely, 2) to express the parametric solution in a Concise Form suitable for theoretical and numerical analysis, and 3) to find simplified systems which show characteristic features of the system. The block triangularization is a standard technique in solving the sparse linear systems. In this paper, we attack the above problems by introducing a concept of local blocks. The conventional block corresponds to a strongly connected maximal subgraph of the associated directed graph for the coefficient matrix, and our local blocks correspond to strongly connected non-maximal subgraphs. By determining local blocks in a nested way and solving subsystems from low to higher ones, we replace sub-expressions by solver parameters systematically, obtaining the solution in a Concise Form. Furthermore, we show an idea to Form simple systems which show characteristic features of the whole system.

  • CASC - Solving Parametric Sparse Linear Systems by Local Blocking
    Computer Algebra in Scientific Computing, 2014
    Co-Authors: Tateaki Sasaki, Daiju Inaba, Fujio Kako
    Abstract:

    In solving parametric sparse linear systems, we want 1) to know relations on parametric coefficients which change the system largely, 2) to express the parametric solution in a Concise Form suitable for theoretical and numerical analysis, and 3) to find simplified systems which show characteristic features of the system. The block triangularization is a standard technique in solving the sparse linear systems. In this paper, we attack the above problems by introducing a concept of local blocks. The conventional block corresponds to a strongly connected maximal subgraph of the associated directed graph for the coefficient matrix, and our local blocks correspond to strongly connected non-maximal subgraphs. By determining local blocks in a nested way and solving subsystems from low to higher ones, we replace sub-expressions by solver parameters systematically, obtaining the solution in a Concise Form. Furthermore, we show an idea to Form simple systems which show characteristic features of the whole system.