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  2. 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.

  3. 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.

  4. Divided differences - Wikipedia

    en.wikipedia.org/wiki/Divided_differences

    This is known as Opitz' formula. [2] [3] Now consider increasing the degree of to infinity, i.e. turn the Taylor polynomial into a Taylor series. Let be a function which corresponds to a power series.

  5. Linear approximation - Wikipedia

    en.wikipedia.org/wiki/Linear_approximation

    Given a twice continuously differentiable function of one real variable, Taylor's theorem for the case = states that = + ′ () + where is the remainder term. The linear approximation is obtained by dropping the remainder: f ( x ) ≈ f ( a ) + f ′ ( a ) ( x − a ) . {\displaystyle f(x)\approx f(a)+f'(a)(x-a).}

  6. 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 ...

  7. Automatic differentiation - Wikipedia

    en.wikipedia.org/wiki/Automatic_differentiation

    Instead, truncated Taylor polynomial algebra can be used. The resulting arithmetic, defined on generalized dual numbers, allows efficient computation using functions as if they were a data type. Once the Taylor polynomial of a function is known, the derivatives are easily extracted.

  8. Euler numbers - Wikipedia

    en.wikipedia.org/wiki/Euler_numbers

    where ⁡ is the hyperbolic cosine function. The Euler numbers are related to a special value of the Euler polynomials, namely: = (). The Euler numbers appear in the Taylor series expansions of the secant and hyperbolic secant functions. The latter is the function in the definition.

  9. Differential calculus - Wikipedia

    en.wikipedia.org/wiki/Differential_calculus

    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. Taylor's theorem gives a precise bound on how good the approximation is. If f is a polynomial of degree less than or equal to d, then the Taylor polynomial of degree d equals f ...