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  2. 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]

  3. 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 ...

  4. Zeros and poles - Wikipedia

    en.wikipedia.org/wiki/Zeros_and_poles

    In this case a point that is neither a pole nor a zero is viewed as a pole (or zero) of order 0. A meromorphic function may have infinitely many zeros and poles. This is the case for the gamma function (see the image in the infobox), which is meromorphic in the whole complex plane, and has a simple pole at every non-positive integer.

  5. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    An illustration of Newton's method. In numerical analysis, the Newton–Raphson method, also known simply as Newton's method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes) of a real-valued function.

  6. Quasi-Newton method - Wikipedia

    en.wikipedia.org/wiki/Quasi-Newton_method

    Newton's method to find zeroes of a function of multiple variables is given by + = [()] (), where [()] is the left inverse of the Jacobian matrix of evaluated for .. Strictly speaking, any method that replaces the exact Jacobian () with an approximation is a quasi-Newton method. [1]

  7. Bisection method - Wikipedia

    en.wikipedia.org/wiki/Bisection_method

    The input for the method is a continuous function f, an interval [a, b], and the function values f(a) and f(b). The function values are of opposite sign (there is at least one zero crossing within the interval). Each iteration performs these steps: Calculate c, the midpoint of the interval, c = ⁠ a + b / 2 ⁠.

  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. 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 ...