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  2. Conjugate gradient method - Wikipedia

    en.wikipedia.org/wiki/Conjugate_gradient_method

    Conjugate gradient, assuming exact arithmetic, converges in at most n steps, where n is the size of the matrix of the system (here n = 2). In mathematics , the conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations , namely those whose matrix is positive-semidefinite .

  3. Derivation of the conjugate gradient method - Wikipedia

    en.wikipedia.org/wiki/Derivation_of_the...

    The conjugate direction method is imprecise in the sense that no formulae are given for selection of the directions ,,, …. Specific choices lead to various methods including the conjugate gradient method and Gaussian elimination.

  4. Nonlinear conjugate gradient method - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_conjugate...

    Whereas linear conjugate gradient seeks a solution to the linear equation =, the nonlinear conjugate gradient method is generally used to find the local minimum of a nonlinear function using its gradient alone. It works when the function is approximately quadratic near the minimum, which is the case when the function is twice differentiable at ...

  5. Barzilai-Borwein method - Wikipedia

    en.wikipedia.org/wiki/Barzilai-Borwein_method

    The Barzilai-Borwein method [1] is an iterative gradient descent method for unconstrained optimization using either of two step sizes derived from the linear trend of the most recent two iterates. This method, and modifications, are globally convergent under mild conditions, [ 2 ] [ 3 ] and perform competitively with conjugate gradient methods ...

  6. Preconditioner - Wikipedia

    en.wikipedia.org/wiki/Preconditioner

    The two-sided preconditioned system ... Typical examples involve using non-linear iterative methods, e.g., the conjugate gradient method, as a part of the ...

  7. Iterative method - Wikipedia

    en.wikipedia.org/wiki/Iterative_method

    The prototypical method in this class is the conjugate gradient method (CG) which assumes that the system matrix is symmetric positive-definite. For symmetric (and possibly indefinite) A {\displaystyle A} one works with the minimal residual method (MINRES).

  8. Biconjugate gradient method - Wikipedia

    en.wikipedia.org/wiki/Biconjugate_gradient_method

    In mathematics, more specifically in numerical linear algebra, the biconjugate gradient method is an algorithm to solve systems of linear equations A x = b . {\displaystyle Ax=b.\,} Unlike the conjugate gradient method , this algorithm does not require the matrix A {\displaystyle A} to be self-adjoint , but instead one needs to perform ...

  9. Topological conjugacy - Wikipedia

    en.wikipedia.org/wiki/Topological_conjugacy

    In mathematics, two functions are said to be topologically conjugate if there exists a homeomorphism that will conjugate the one into the other. Topological conjugacy, and related-but-distinct § Topological equivalence of flows, are important in the study of iterated functions and more generally dynamical systems, since, if the dynamics of one iterative function can be determined, then that ...