enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Taylor's theorem - Wikipedia

    en.wikipedia.org/wiki/Taylor's_theorem

    In calculus, Taylor's theorem gives an approximation of a -times differentiable function around a given point by a polynomial of degree , called the -th-order Taylor polynomial. For a smooth function , the Taylor polynomial is the truncation at the order k {\textstyle k} of the Taylor series of the function.

  3. Taylor series - Wikipedia

    en.wikipedia.org/wiki/Taylor_series

    The sine function (blue) is closely approximated by its Taylor polynomial of degree 7 (pink) for a full period centered at the origin. The Taylor polynomials for ln(1 + x) only provide accurate approximations in the range −1 < x ≤ 1. For x > 1, Taylor polynomials of higher degree provide worse approximations.

  4. Order of approximation - Wikipedia

    en.wikipedia.org/wiki/Order_of_approximation

    For example, if a quantity is constant within the whole interval, approximating it with a second-order Taylor series will not increase the accuracy. In the case of a smooth function, the nth-order approximation is a polynomial of degree n, which is obtained by truncating the Taylor series

  5. Universal Taylor series - Wikipedia

    en.wikipedia.org/wiki/Universal_Taylor_series

    Thus to -approximate () = using a polynomial with lowest degree 3, we do so for () with < / by truncating its Taylor expansion. Now iterate this construction by plugging in the lowest-degree-3 approximation into the Taylor expansion of g ( x ) {\displaystyle g(x)} , obtaining an approximation of lowest degree 9, 27, 81...

  6. Bramble–Hilbert lemma - Wikipedia

    en.wikipedia.org/wiki/Bramble–Hilbert_lemma

    is the Taylor polynomial of degree at most of centered at evaluated at , and is a function that has derivatives of all orders, equals to zero outside of , and such that ∫ B ψ d x = 1. {\displaystyle \int _{B}\psi \,dx=1.}

  7. Polynomial interpolation - Wikipedia

    en.wikipedia.org/wiki/Polynomial_interpolation

    In numerical analysis, polynomial interpolation is the interpolation of a given bivariate data set by the polynomial of lowest possible degree that passes through the points of the dataset. [ 1 ]

  8. Finite difference method - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_method

    Where n! denotes the factorial of n, and R n (x) is a remainder term, denoting the difference between the Taylor polynomial of degree n and the original function. Following is the process to derive an approximation for the first derivative of the function f by first truncating the Taylor polynomial plus remainder: f ( x 0 + h ) = f ( x 0 ) + f ...

  9. Differential calculus - Wikipedia

    en.wikipedia.org/wiki/Differential_calculus

    c should always be ⁠ f''(x 0) / 2 ⁠, and d should always be ⁠ f'''(x 0) / 3! ⁠. Using these coefficients gives the Taylor polynomial of f. The Taylor polynomial of degree d is the polynomial of degree d which best approximates f, and its coefficients can be found by a generalization of the above formulas.