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A variant of Gaussian elimination called Gauss–Jordan elimination can be used for finding the inverse of a matrix, if it exists. If A is an n × n square matrix, then one can use row reduction to compute its inverse matrix, if it exists. First, the n × n identity matrix is augmented to the right of A, forming an n × 2n block matrix [A | I].
Elimination theory culminated with the work of Leopold Kronecker, and finally Macaulay, who introduced multivariate resultants and U-resultants, providing complete elimination methods for systems of polynomial equations, which are described in the chapter on Elimination theory in the first editions (1930) of van der Waerden's Moderne Algebra.
The solution method called "Fang Cheng Shi" is best known today as Gaussian elimination. Among the eighteen problems listed in the Fang Cheng chapter, some are equivalent to simultaneous linear equations with two unknowns, some are equivalent to simultaneous linear equations with 3 unknowns, and the most complex example analyzes the solution to ...
Subsequently, many mathematicians were performing and perfecting it yet as the method became relegated to school grade, few of them left any detailed descriptions. Thus the name Gaussian elimination is only a convenient abbreviation of a complex history. The LU decomposition was introduced by the Polish astronomer Tadeusz Banachiewicz in 1938. [4]
Having enough such pairs, using Gaussian elimination, one can get products of certain r and of the corresponding s to be squares at the same time. A slightly stronger condition is needed—that they are norms of squares in our number fields, but that condition can be achieved by this method too.
In numerical linear algebra, the tridiagonal matrix algorithm, also known as the Thomas algorithm (named after Llewellyn Thomas), is a simplified form of Gaussian elimination that can be used to solve tridiagonal systems of equations. A tridiagonal system for n unknowns may be written as
Gaussian elimination; Gauss–Jordan elimination: solves systems of linear equations; Gauss–Seidel method: solves systems of linear equations iteratively; Levinson recursion: solves equation involving a Toeplitz matrix; Stone's method: also known as the strongly implicit procedure or SIP, is an algorithm for solving a sparse linear system of ...
Runge–Kutta–Fehlberg method — a fifth-order method with six stages and an embedded fourth-order method; Gauss–Legendre method — family of A-stable method with optimal order based on Gaussian quadrature; Butcher group — algebraic formalism involving rooted trees for analysing Runge–Kutta methods; List of Runge–Kutta methods