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  2. Functional equation - Wikipedia

    en.wikipedia.org/wiki/Functional_equation

    Some classes of functional equations can be solved by computer-assisted techniques. [vague] [4] In dynamic programming a variety of successive approximation methods [5] [6] are used to solve Bellman's functional equation, including methods based on fixed point iterations.

  3. Fixed-point iteration - Wikipedia

    en.wikipedia.org/wiki/Fixed-point_iteration

    The fixed point iteration x n+1 = cos x n with initial value x 1 = −1.. An attracting fixed point of a function f is a fixed point x fix of f with a neighborhood U of "close enough" points around x fix such that for any value of x in U, the fixed-point iteration sequence , (), (()), ((())), … is contained in U and converges to x fix.

  4. 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.

  5. 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.

  6. Root-finding algorithm - Wikipedia

    en.wikipedia.org/wiki/Root-finding_algorithm

    Solving an equation f(x) = g(x) is the same as finding the roots of the function h(x) = f(x) – g(x). Thus root-finding algorithms can be used to solve any equation of continuous functions. However, most root-finding algorithms do not guarantee that they will find all roots of a function, and if such an algorithm does not find any root, that ...

  7. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    In the formulation given above, the scalars x n are replaced by vectors x n and instead of dividing the function f(x n) by its derivative f ′ (x n) one instead has to left multiply the function F(x n) by the inverse of its k × k Jacobian matrix J F (x n). [20] [21] [22] This results in the expression

  8. Secant method - Wikipedia

    en.wikipedia.org/wiki/Secant_method

    The red curve shows the function f, and the blue lines are the secants. For this particular case, the secant method will not converge to the visible root. In numerical analysis, the secant method is a root-finding algorithm that uses a succession of roots of secant lines to better approximate a root of a function f.

  9. Quartic function - Wikipedia

    en.wikipedia.org/wiki/Quartic_function

    be the general quartic equation we want to solve. Dividing by a 4, provides the equivalent equation x 4 + bx 3 + cx 2 + dx + e = 0, with b = ⁠ a 3 / a 4 ⁠, c = ⁠ a 2 / a 4 ⁠, d = ⁠ a 1 / a 4 ⁠, and e = ⁠ a 0 / a 4 ⁠. Substituting y − ⁠ b / 4 ⁠ for x gives, after regrouping the terms, the equation y 4 + py 2 + qy + r = 0, where