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  2. Transcendental equation - Wikipedia

    en.wikipedia.org/wiki/Transcendental_equation

    Approximate numerical solutions to transcendental equations can be found using numerical, analytical approximations, or graphical methods. Numerical methods for solving arbitrary equations are called root-finding algorithms. In some cases, the equation can be well approximated using Taylor series near the zero.

  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. Numerical analysis - Wikipedia

    en.wikipedia.org/wiki/Numerical_analysis

    Root-finding algorithms are used to solve nonlinear equations (they are so named since a root of a function is an argument for which the function yields zero). If the function is differentiable and the derivative is known, then Newton's method is a popular choice. [16] [17] Linearization is another technique for solving nonlinear equations.

  5. Simplex algorithm - Wikipedia

    en.wikipedia.org/wiki/Simplex_algorithm

    The storage and computation overhead is such that the standard simplex method is a prohibitively expensive approach to solving large linear programming problems. In each simplex iteration, the only data required are the first row of the tableau, the (pivotal) column of the tableau corresponding to the entering variable and the right-hand-side.

  6. Mandelbrot set - Wikipedia

    en.wikipedia.org/wiki/Mandelbrot_set

    The Mandelbrot set (/ ˈ m æ n d əl b r oʊ t,-b r ɒ t /) [1] [2] is a two-dimensional set with a relatively simple definition that exhibits great complexity, especially as it is magnified.

  7. Muller's method - Wikipedia

    en.wikipedia.org/wiki/Muller's_method

    Muller's method is a root-finding algorithm, a numerical method for solving equations of the form f(x) = 0.It was first presented by David E. Muller in 1956.. Muller's method is based on the secant method, which constructs at every iteration a line through two points on the graph of f.

  8. Quartic equation - Wikipedia

    en.wikipedia.org/wiki/Quartic_equation

    This is a cubic equation in y. 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.

  9. Brent's method - Wikipedia

    en.wikipedia.org/wiki/Brent's_method

    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. If f is continuous on [a 0, b 0], the intermediate value theorem guarantees the existence of a solution between a 0 and b 0.

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