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  2. Fixed-point iteration - Wikipedia

    en.wikipedia.org/wiki/Fixed-point_iteration

    In numerical analysis, fixed-point iteration is a method of computing fixed points of a function.. More specifically, given a function defined on the real numbers with real values and given a point in the domain of , the fixed-point iteration is + = (), =,,, … which gives rise to the sequence,,, … of iterated function applications , (), (()), … which is hoped to converge to a point .

  3. Functional equation - Wikipedia

    en.wikipedia.org/wiki/Functional_equation

    In mathematics, a functional equation [1] [2] [irrelevant citation] is, in the broadest meaning, an equation in which one or several functions appear as unknowns.So, differential equations and integral equations are functional equations.

  4. Equation solving - Wikipedia

    en.wikipedia.org/wiki/Equation_solving

    An example of using Newton–Raphson method to solve numerically the equation f(x) = 0. In mathematics, to solve an equation is to find its solutions, which are the values (numbers, functions, sets, etc.) that fulfill the condition stated by the equation, consisting generally of two expressions related by an equals sign.

  5. Iterative method - Wikipedia

    en.wikipedia.org/wiki/Iterative_method

    If an equation can be put into the form f(x) = x, and a solution x is an attractive fixed point of the function f, then one may begin with a point x 1 in the basin of attraction of x, and let x n+1 = f(x n) for n ≥ 1, and the sequence {x n} n ≥ 1 will converge to the solution x.

  6. Iterated function - Wikipedia

    en.wikipedia.org/wiki/Iterated_function

    If f and g are two iterated functions, and there exists a homeomorphism h such that g = h −1 f h, then f and g are said to be topologically conjugate. Clearly, topological conjugacy is preserved under iteration, as g n = h −1 f n h. Thus, if one can solve for one iterated function system, one also has solutions for all topologically ...

  7. Lagrange multiplier - Wikipedia

    en.wikipedia.org/wiki/Lagrange_multiplier

    In mathematical optimization, the method of Lagrange multipliers is a strategy for finding the local maxima and minima of a function subject to equation constraints (i.e., subject to the condition that one or more equations have to be satisfied exactly by the chosen values of the variables). [1]

  8. How to Solve It - Wikipedia

    en.wikipedia.org/wiki/How_to_Solve_It

    Russian inventor Genrich Altshuller developed an elaborate set of methods for problem solving known as TRIZ, which in many aspects reproduces or parallels Pólya's work. How to Solve it by Computer is a computer science book by R. G. Dromey. [29] It was inspired by Pólya's work.

  9. Quartic equation - Wikipedia

    en.wikipedia.org/wiki/Quartic_equation

    Solve for y using any method for solving such equations (e.g. conversion to a reduced cubic and application of Cardano's formula). Any of the three possible roots will do. Any of the three possible roots will do.