39 relations: Algorithm, Attractor, Basis (linear algebra), Biconjugate gradient method, Carl Friedrich Gauss, Computational mathematics, Conjugate gradient method, Cornelius Lanczos, David M. Young Jr., Differentiable function, Eduard Stiefel, Fixed point (mathematics), Gauss–Seidel method, Gaussian elimination, Generalized minimal residual method, Heuristic, Invertible matrix, Iterative method, Jacobi method, Krylov subspace, Magnus Hestenes, Matrix splitting, Modified Richardson iteration, Nonlinear system, Operator (mathematics), Partial differential equation, Positive-definite matrix, Preconditioner, Relaxation (iterative method), Residual (numerical analysis), Root-finding algorithm, Round-off error, Spectral radius, Spectrum (functional analysis), Successive over-relaxation, Symmetric matrix, Symmetric successive over-relaxation, System of linear equations, Triangular matrix.
In mathematics and computer science, an algorithm is an unambiguous specification of how to solve a class of problems.
In the mathematical field of dynamical systems, an attractor is a set of numerical values toward which a system tends to evolve, for a wide variety of starting conditions of the system.
In mathematics, a set of elements (vectors) in a vector space V is called a basis, or a set of, if the vectors are linearly independent and every vector in the vector space is a linear combination of this set.
In mathematics, more specifically in numerical linear algebra, the biconjugate gradient method is an algorithm to solve systems of linear equations Unlike the conjugate gradient method, this algorithm does not require the matrix A to be self-adjoint, but instead one needs to perform multiplications by the conjugate transpose.
Johann Carl Friedrich Gauss (Gauß; Carolus Fridericus Gauss; 30 April 177723 February 1855) was a German mathematician and physicist who made significant contributions to many fields, including algebra, analysis, astronomy, differential geometry, electrostatics, geodesy, geophysics, magnetic fields, matrix theory, mechanics, number theory, optics and statistics.
Computational mathematics may refer to two different aspect of the relation between computing and mathematics.
In mathematics, the conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations, namely those whose matrix is symmetric and positive-definite.
Cornelius (Cornel) Lanczos (Lánczos Kornél,, born as Kornél Lőwy, until 1906: Löwy (Lőwy) Kornél) was a Jewish Hungarian mathematician and physicist, who was born on February 2, 1893, and died on June 25, 1974.
David M. Young Jr. (October 20, 1923 – December 21, 2008) was an American mathematician and computer scientist who was one of the pioneers in the field of modern numerical analysis/scientific computing.
In calculus (a branch of mathematics), a differentiable function of one real variable is a function whose derivative exists at each point in its domain.
Eduard L. Stiefel (21 April 1909 – 25 November 1978) was a Swiss mathematician.
In mathematics, a fixed point (sometimes shortened to fixpoint, also known as an invariant point) of a function is an element of the function's domain that is mapped to itself by the function.
In numerical linear algebra, the Gauss–Seidel method, also known as the Liebmann method or the method of successive displacement, is an iterative method used to solve a linear system of equations.
In linear algebra, Gaussian elimination (also known as row reduction) is an algorithm for solving systems of linear equations.
In mathematics, the generalized minimal residual method (GMRES) is an iterative method for the numerical solution of a nonsymmetric system of linear equations.
A heuristic technique (εὑρίσκω, "find" or "discover"), often called simply a heuristic, is any approach to problem solving, learning, or discovery that employs a practical method, not guaranteed to be optimal, perfect, logical, or rational, but instead sufficient for reaching an immediate goal.
In linear algebra, an n-by-n square matrix A is called invertible (also nonsingular or nondegenerate) if there exists an n-by-n square matrix B such that where In denotes the n-by-n identity matrix and the multiplication used is ordinary matrix multiplication.
In computational mathematics, an iterative method is a mathematical procedure that uses an initial guess to generate a sequence of improving approximate solutions for a class of problems, in which the n-th approximation is derived from the previous ones.
In numerical linear algebra, the Jacobi method (or Jacobi iterative method) is an algorithm for determining the solutions of a diagonally dominant system of linear equations.
In linear algebra, the order-r Krylov subspace generated by an n-by-n matrix A and a vector b of dimension n is the linear subspace spanned by the images of b under the first r powers of A (starting from A^0.
Magnus Rudolph Hestenes (February 13, 1906 – May 31, 1991) was an American mathematician.
In the mathematical discipline of numerical linear algebra, a matrix splitting is an expression which represents a given matrix as a sum or difference of matrices.
Modified Richardson iteration is an iterative method for solving a system of linear equations.
In mathematics and science, a nonlinear system is a system in which the change of the output is not proportional to the change of the input.
In mathematics, an operator is generally a mapping that acts on the elements of a space to produce other elements of the same space.
In mathematics, a partial differential equation (PDE) is a differential equation that contains unknown multivariable functions and their partial derivatives.
In linear algebra, a symmetric real matrix M is said to be positive definite if the scalar z^Mz is strictly positive for every non-zero column vector z of n real numbers.
In mathematics, preconditioning is the application of a transformation, called the preconditioner, that conditions a given problem into a form that is more suitable for numerical solving methods.
In numerical mathematics, relaxation methods are iterative methods for solving systems of equations, including nonlinear systems.
Loosely speaking, a residual is the error in a result.
In mathematics and computing, a root-finding algorithm is an algorithm for finding roots of continuous functions.
A round-off error, also called rounding error, is the difference between the calculated approximation of a number and its exact mathematical value due to rounding.
In mathematics, the spectral radius of a square matrix or a bounded linear operator is the largest absolute value of its eigenvalues (i.e. supremum among the absolute values of the elements in its spectrum).
In mathematics, particularly in functional analysis, the spectrum of a bounded operator is a generalisation of the set of eigenvalues of a matrix.
In numerical linear algebra, the method of successive over-relaxation (SOR) is a variant of the Gauss–Seidel method for solving a linear system of equations, resulting in faster convergence.
In linear algebra, a symmetric matrix is a square matrix that is equal to its transpose.
In applied mathematics, symmetric successive over-relaxation (SSOR), is a preconditioner.
In mathematics, a system of linear equations (or linear system) is a collection of two or more linear equations involving the same set of variables.
In the mathematical discipline of linear algebra, a triangular matrix is a special kind of square matrix.
Direct method (computational mathematics), Iteration algorithm, Iteration methods, Iteration scheme, Iterative algorithm, Iterative approximation, Iterative convergence, Iterative methods, Iterative procedure, Iterative solver, Krylov subspace method, Krylov subspace methods.