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  2. Fourier–Motzkin elimination - Wikipedia

    en.wikipedia.org/wiki/Fourier–Motzkin_elimination

    Since all the inequalities are in the same form (all less-than or all greater-than), we can examine the coefficient signs for each variable. Eliminating x would yield 2*2 = 4 inequalities on the remaining variables, and so would eliminating y. Eliminating z would yield only 3*1 = 3 inequalities so we use that instead.

  3. Polynomial root-finding algorithms - Wikipedia

    en.wikipedia.org/wiki/Polynomial_root-finding...

    This is illustrated by Wilkinson's polynomial: the roots of this polynomial of degree 20 are the 20 first positive integers; changing the last bit of the 32-bit representation of one of its coefficient (equal to –210) produces a polynomial with only 10 real roots and 10 complex roots with imaginary parts larger than 0.6.

  4. Durand–Kerner method - Wikipedia

    en.wikipedia.org/wiki/Durand–Kerner_method

    In numerical analysis, the Weierstrass method or Durand–Kerner method, discovered by Karl Weierstrass in 1891 and rediscovered independently by Durand in 1960 and Kerner in 1966, is a root-finding algorithm for solving polynomial equations. [1] In other words, the method can be used to solve numerically the equation f(x) = 0,

  5. Laguerre's method - Wikipedia

    en.wikipedia.org/wiki/Laguerre's_method

    If x is a simple root of the polynomial , then Laguerre's method converges cubically whenever the initial guess, , is close enough to the root . On the other hand, when x 1 {\displaystyle \ x_{1}\ } is a multiple root convergence is merely linear, with the penalty of calculating values for the polynomial and its first and second derivatives at ...

  6. Brent's method - Wikipedia

    en.wikipedia.org/wiki/Brent's_method

    In the fifth iteration, inverse quadratic interpolation yields −3.45500, which lies in the required interval. However, the previous iteration was a bisection step, so the inequality |−3.45500 − b 4 | ≤ |b 4 − b 3 | / 2 need to be satisfied. This inequality is false, so we use the midpoint m = −3.35724.

  7. Root-finding algorithm - Wikipedia

    en.wikipedia.org/wiki/Root-finding_algorithm

    The simplest root-finding algorithm is the bisection method. Let f be a continuous function for which one knows an interval [a, b] such that f(a) and f(b) have opposite signs (a bracket). Let c = (a +b)/2 be the middle of the interval (the midpoint or the point that bisects

  8. Bairstow's method - Wikipedia

    en.wikipedia.org/wiki/Bairstow's_method

    In numerical analysis, Bairstow's method is an efficient algorithm for finding the roots of a real polynomial of arbitrary degree. The algorithm first appeared in the appendix of the 1920 book Applied Aerodynamics by Leonard Bairstow. [1] [non-primary source needed] The algorithm finds the roots in complex conjugate pairs using only real ...

  9. Frobenius method - Wikipedia

    en.wikipedia.org/wiki/Frobenius_method

    If the root is repeated or the roots differ by an integer, then the second solution can be found using: = ⁡ + = + where () is the first solution (based on the larger root in the case of unequal roots), is the smaller root, and the constant C and the coefficients are to be determined.