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  2. Rate of convergence - Wikipedia

    en.wikipedia.org/wiki/Rate_of_convergence

    These are linear, quadratic, and cubic polynomial expressions when is 1, 2, and 3 ... is called quadratic convergence and the sequence is said to converge ...

  3. Linear recurrence with constant coefficients - Wikipedia

    en.wikipedia.org/wiki/Linear_recurrence_with...

    In mathematics (including combinatorics, linear algebra, and dynamical systems), a linear recurrence with constant coefficients [1]: ch. 17 [2]: ch. 10 (also known as a linear recurrence relation or linear difference equation) sets equal to 0 a polynomial that is linear in the various iterates of a variable—that is, in the values of the elements of a sequence.

  4. Conjugate gradient method - Wikipedia

    en.wikipedia.org/wiki/Conjugate_gradient_method

    A comparison of the convergence of gradient descent with optimal step size (in green) and conjugate vector (in red) for minimizing a quadratic function associated with a given linear system. Conjugate gradient, assuming exact arithmetic, converges in at most n steps, where n is the size of the matrix of the system (here n = 2).

  5. Interior-point method - Wikipedia

    en.wikipedia.org/wiki/Interior-point_method

    An interior point method was discovered by Soviet mathematician I. I. Dikin in 1967. [1] The method was reinvented in the U.S. in the mid-1980s. In 1984, Narendra Karmarkar developed a method for linear programming called Karmarkar's algorithm, [2] which runs in provably polynomial time (() operations on L-bit numbers, where n is the number of variables and constants), and is also very ...

  6. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    The following iterates are 1.0103, 1.00093, 1.0000082, and 1.00000000065, illustrating quadratic convergence. This highlights that quadratic convergence of a Newton iteration does not mean that only few iterates are required; this only applies once the sequence of iterates is sufficiently close to the root. [16]

  7. Approximation theory - Wikipedia

    en.wikipedia.org/wiki/Approximation_theory

    Convergence is quadratic for well-behaved functions—if the test points are within of the correct result, they will be approximately within of the correct result after the next round. Remez's algorithm is typically started by choosing the extrema of the Chebyshev polynomial T N + 1 {\displaystyle T_{N+1}} as the initial points, since the final ...

  8. Bairstow's method - Wikipedia

    en.wikipedia.org/wiki/Bairstow's_method

    Bairstow's algorithm inherits the local quadratic convergence of Newton's method, except in the case of quadratic factors of multiplicity higher than 1, when convergence to that factor is linear. A particular kind of instability is observed when the polynomial has odd degree and only one real root.

  9. Logistic map - Wikipedia

    en.wikipedia.org/wiki/Logistic_map

    Chaos is not peculiar to non-linear systems alone and it can also be exhibited by infinite dimensional linear systems. [11] As mentioned above, the logistic map itself is an ordinary quadratic function. An important question in terms of dynamical systems is how the behavior of the trajectory changes when the parameter r changes.

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