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  2. Gauss–Seidel method - Wikipedia

    en.wikipedia.org/wiki/Gauss–Seidel_method

    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 system of linear equations. It is named after the German mathematicians Carl Friedrich Gauss and Philipp Ludwig von Seidel .

  3. System of equations - Wikipedia

    en.wikipedia.org/wiki/System_of_equations

    In mathematics, a set of simultaneous equations, also known as a system of equations or an equation system, is a finite set of equations for which common solutions are sought.

  4. Petrov–Galerkin method - Wikipedia

    en.wikipedia.org/wiki/Petrov–Galerkin_method

    The Petrov–Galerkin method is a mathematical method used to approximate solutions of partial differential equations which contain terms with odd order and where the test function and solution function belong to different function spaces. [1]

  5. File:Binary search vs Linear search example.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Binary_search_vs...

    Example comparing two search algorithms. To look for "Morin, Arthur" in some ficitious participant list, linear search needs 28 checks, while binary search needs 5. Svg version: File:Binary search vs Linear search example svg.svg.

  6. Reynolds-averaged Navier–Stokes equations - Wikipedia

    en.wikipedia.org/wiki/Reynolds-averaged_Navier...

    The Reynolds-averaged Navier–Stokes equations (RANS equations) are time-averaged [a] equations of motion for fluid flow.The idea behind the equations is Reynolds decomposition, whereby an instantaneous quantity is decomposed into its time-averaged and fluctuating quantities, an idea first proposed by Osborne Reynolds. [1]

  7. Regularization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Regularization_(mathematics)

    When learning a linear function , characterized by an unknown vector such that () =, one can add the -norm of the vector to the loss expression in order to prefer solutions with smaller norms. Tikhonov regularization is one of the most common forms.