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  2. Root-finding algorithm - Wikipedia

    en.wikipedia.org/wiki/Root-finding_algorithm

    A zero of a function f is a number x such that f(x) = 0. As, generally, the zeros of a function cannot be computed exactly nor expressed in closed form, root-finding algorithms provide approximations to zeros. For functions from the real numbers to real numbers or from the complex numbers to the complex numbers, these are expressed either as ...

  3. Zero of a function - Wikipedia

    en.wikipedia.org/wiki/Zero_of_a_function

    In mathematics, a zero (also sometimes called a root) of a real-, complex-, or generally vector-valued function, is a member of the domain of such that () vanishes at ; that is, the function attains the value of 0 at , or equivalently, is a solution to the equation () =. [1] A "zero" of a function is thus an input value that produces an output ...

  4. Secant method - Wikipedia

    en.wikipedia.org/wiki/Secant_method

    The secant method is an iterative numerical method for finding a zero of a function f.Given two initial values x 0 and x 1, the method proceeds according to the recurrence relation

  5. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    def f (x): return x ** 2-2 # f(x) = x^2 - 2 def f_prime (x): return 2 * x # f'(x) = 2x def newtons_method (x0, f, f_prime, tolerance, epsilon, max_iterations): """Newton's method Args: x0: The initial guess f: The function whose root we are trying to find f_prime: The derivative of the function tolerance: Stop when iterations change by less ...

  6. Chebyshev nodes - Wikipedia

    en.wikipedia.org/wiki/Chebyshev_nodes

    This product is a monic polynomial of degree n. It may be shown that the maximum absolute value (maximum norm) of any such polynomial is bounded from below by 2 1n. This bound is attained by the scaled Chebyshev polynomials 2 1n T n, which are also monic. (Recall that |T n (x)| ≤ 1 for x ∈ [−1, 1]. [5])

  7. Jenkins–Traub algorithm - Wikipedia

    en.wikipedia.org/wiki/Jenkins–Traub_algorithm

    The Jenkins–Traub algorithm for polynomial zeros is a fast globally convergent iterative polynomial root-finding method published in 1970 by Michael A. Jenkins and Joseph F. Traub. They gave two variants, one for general polynomials with complex coefficients, commonly known as the "CPOLY" algorithm, and a more complicated variant for the ...

  8. Brent's method - Wikipedia

    en.wikipedia.org/wiki/Brent's_method

    The idea to combine the bisection method with the secant method goes back to Dekker (1969).. Suppose that we want to solve the equation f(x) = 0.As with the bisection method, we need to initialize Dekker's method with two points, say a 0 and b 0, such that f(a 0) and f(b 0) have opposite signs.

  9. Rational root theorem - Wikipedia

    en.wikipedia.org/wiki/Rational_root_theorem

    In the polynomial + the only possible rational roots would have a numerator that divides 6 and a denominator that divides 1, limiting the possibilities to ±1, ±2, ±3, and ±6. Of these, 1, 2, and –3 equate the polynomial to zero, and hence are its rational roots (in fact these are its only roots since a cubic polynomial has only three roots).