In the process of solving the linear epuation by the Gaussian Elimination or other comparable technigues, a computational interest is the pivotal ordering of the coefficient matix for the given set of epuations. This paper describes the algorithm fit for a large scale sparse matrices. The algorithm is essentially so called "minimum fill-in" but the method to obtain the minimum fill-in is unigue and some other criteria are added in oder to improve the optimality. Comparisions are made withe Ghausi method by actual program and results are given
We propose several techniques as alternatives to partial pivoting to stabilize sparse Gaussian elimi...
A FORTRAN 77 implementation of a Gauss algorithm with partial pivoting for banded matrices is descri...
A FORTRAN 77 implementation of a Gauss algorithm with partial pivoting for banded matrices is descri...
The coefficient matrix of a very large system of equations is generally very sparse, i. e., non-zero...
As the standard method for solving systems of linear equations, Gaussian elimination (GE) is one of ...
International audienceThis paper considers elimination algorithms for sparse matrices over finite fi...
International audienceThis paper considers elimination algorithms for sparse matrices over finite fi...
International audienceThis paper considers elimination algorithms for sparse matrices over finite fi...
AbstractThis paper discusses a method for determining a good pivoting sequence for Gaussian eliminat...
This paper surveys some of the recent research on the applications of the algebraic and combinatoria...
Existing sparse partial pivoting algorithms can spend asymptomatically more time manipulating data ...
For large scale problems in electric circuit simulation as well as in chemical process simulation, t...
AbstractA variant of the fraction free form of Gaussian elimination is presented. This algorithm red...
AbstractThis paper discusses a method for determining a good pivoting sequence for Gaussian eliminat...
AbstractA variant of the fraction free form of Gaussian elimination is presented. This algorithm red...
We propose several techniques as alternatives to partial pivoting to stabilize sparse Gaussian elimi...
A FORTRAN 77 implementation of a Gauss algorithm with partial pivoting for banded matrices is descri...
A FORTRAN 77 implementation of a Gauss algorithm with partial pivoting for banded matrices is descri...
The coefficient matrix of a very large system of equations is generally very sparse, i. e., non-zero...
As the standard method for solving systems of linear equations, Gaussian elimination (GE) is one of ...
International audienceThis paper considers elimination algorithms for sparse matrices over finite fi...
International audienceThis paper considers elimination algorithms for sparse matrices over finite fi...
International audienceThis paper considers elimination algorithms for sparse matrices over finite fi...
AbstractThis paper discusses a method for determining a good pivoting sequence for Gaussian eliminat...
This paper surveys some of the recent research on the applications of the algebraic and combinatoria...
Existing sparse partial pivoting algorithms can spend asymptomatically more time manipulating data ...
For large scale problems in electric circuit simulation as well as in chemical process simulation, t...
AbstractA variant of the fraction free form of Gaussian elimination is presented. This algorithm red...
AbstractThis paper discusses a method for determining a good pivoting sequence for Gaussian eliminat...
AbstractA variant of the fraction free form of Gaussian elimination is presented. This algorithm red...
We propose several techniques as alternatives to partial pivoting to stabilize sparse Gaussian elimi...
A FORTRAN 77 implementation of a Gauss algorithm with partial pivoting for banded matrices is descri...
A FORTRAN 77 implementation of a Gauss algorithm with partial pivoting for banded matrices is descri...