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  2. Lagrange inversion theorem - Wikipedia

    en.wikipedia.org/wiki/Lagrange_inversion_theorem

    The theorem was proved by Lagrange [2] and generalized by Hans Heinrich Bürmann, [3] [4] [5] both in the late 18th century. There is a straightforward derivation using complex analysis and contour integration ; [ 6 ] the complex formal power series version is a consequence of knowing the formula for polynomials , so the theory of analytic ...

  3. Inversion (discrete mathematics) - Wikipedia

    en.wikipedia.org/wiki/Inversion_(discrete...

    The inversions of this permutation using element-based notation are: (3, 1), (3, 2), (5, 1), (5, 2), and (5,4). In computer science and discrete mathematics , an inversion in a sequence is a pair of elements that are out of their natural order .

  4. Inverse iteration - Wikipedia

    en.wikipedia.org/wiki/Inverse_iteration

    Calculating the inverse matrix once, and storing it to apply at each iteration is of complexity O(n 3) + k O(n 2). Storing an LU decomposition of ( A − μ I ) {\displaystyle (A-\mu I)} and using forward and back substitution to solve the system of equations at each iteration is also of complexity O ( n 3 ) + k O ( n 2 ).

  5. Computational complexity of mathematical operations - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity...

    The complexity of an elementary function is equivalent to that of its inverse, since all elementary functions are analytic and hence invertible by means of Newton's method. In particular, if either exp {\displaystyle \exp } or log {\displaystyle \log } in the complex domain can be computed with some complexity, then that complexity is ...

  6. Inverse quadratic interpolation - Wikipedia

    en.wikipedia.org/wiki/Inverse_quadratic...

    In numerical analysis, inverse quadratic interpolation is a root-finding algorithm, meaning that it is an algorithm for solving equations of the form f(x) = 0. The idea is to use quadratic interpolation to approximate the inverse of f. This algorithm is rarely used on its own, but it is important because it forms part of the popular Brent's method.

  7. Lagrange polynomial - Wikipedia

    en.wikipedia.org/wiki/Lagrange_polynomial

    Solving an interpolation problem leads to a problem in linear algebra amounting to inversion of a matrix. Using a standard monomial basis for our interpolation polynomial () = =, we must invert the Vandermonde matrix to solve () = for the coefficients of ().

  8. List of mathematical series - Wikipedia

    en.wikipedia.org/wiki/List_of_mathematical_series

    An infinite series of any rational function of can be reduced to a finite series of polygamma functions, by use of partial fraction decomposition, [8] as explained here. This fact can also be applied to finite series of rational functions, allowing the result to be computed in constant time even when the series contains a large number of terms.

  9. Möbius inversion formula - Wikipedia

    en.wikipedia.org/wiki/Möbius_inversion_formula

    For example, there is a well known proof relating the Riemann zeta function to the prime zeta function that uses the series-based form of Möbius inversion in the previous equation when =. Namely, by the Euler product representation of ζ ( s ) {\displaystyle \zeta (s)} for ℜ ( s ) > 1 {\displaystyle \Re (s)>1}

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