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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.
One method of solving elementary functional equations is substitution. [citation needed] Some solutions to functional equations have exploited surjectivity, injectivity, oddness, and evenness. [citation needed] Some functional equations have been solved with the use of ansatzes, mathematical induction. [citation needed]
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.
If f is defined on the real numbers, it corresponds, in graphical terms, to a curve in the Euclidean plane, and each fixed-point c corresponds to an intersection of the curve with the line y = x, cf. picture. For example, if f is defined on the real numbers by = +, then 2 is a fixed point of f, because f(2) = 2.
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 ...
The method is applicable for numerically solving the equation f(x) = 0 for the real variable x, where f is a continuous function defined on an interval [a, b] and where f(a) and f(b) have opposite signs.
For a known function f(x), a problem is to solve the functional equation for the function α −1 ≡ h, possibly satisfying additional requirements, such as α −1 (0) = 1. The change of variables s α(x) = Ψ(x), for a real parameter s, brings Abel's equation into the celebrated Schröder's equation, Ψ(f(x)) = s Ψ(x).
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.