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  2. Difference engine - Wikipedia

    en.wikipedia.org/wiki/Difference_engine

    The design has the same precision on all columns, but in calculating polynomials, the precision on the higher-order columns could be lower. A difference engine is an automatic mechanical calculator designed to tabulate polynomial functions. It was designed in the 1820s, and was first created by Charles Babbage.

  3. Polynomial interpolation - Wikipedia

    en.wikipedia.org/wiki/Polynomial_interpolation

    Starting with a few accurately computed data points, the corresponding interpolation polynomial will approximate the function at an arbitrary nearby point. Polynomial interpolation also forms the basis for algorithms in numerical quadrature (Simpson's rule) and numerical ordinary differential equations (multigrid methods).

  4. Neville's algorithm - Wikipedia

    en.wikipedia.org/wiki/Neville's_algorithm

    Given a set of n+1 data points (x i, y i) where no two x i are the same, the interpolating polynomial is the polynomial p of degree at most n with the property p(x i) = y i for all i = 0,...,n. This polynomial exists and it is unique. Neville's algorithm evaluates the polynomial at some point x.

  5. Hermite interpolation - Wikipedia

    en.wikipedia.org/wiki/Hermite_interpolation

    Lagrange interpolation allows computing a polynomial of degree less than n that takes the same value at n given points as a given function. Instead, Hermite interpolation computes a polynomial of degree less than n such that the polynomial and its first few derivatives have the same values at m (fewer than n ) given points as the given function ...

  6. Horner's method - Wikipedia

    en.wikipedia.org/wiki/Horner's_method

    This polynomial is further reduced to = + + which is shown in blue and yields a zero of −5. The final root of the original polynomial may be found by either using the final zero as an initial guess for Newton's method, or by reducing () and solving the linear equation. As can be seen, the expected roots of −8, −5, −3, 2, 3, and 7 were ...

  7. Polynomial evaluation - Wikipedia

    en.wikipedia.org/wiki/Polynomial_evaluation

    This problem arises frequently in practice. In computational geometry, polynomials are used to compute function approximations using Taylor polynomials. In cryptography and hash tables, polynomials are used to compute k-independent hashing. In the former case, polynomials are evaluated using floating-point arithmetic, which is not exact. Thus ...

  8. Curve fitting - Wikipedia

    en.wikipedia.org/wiki/Curve_fitting

    Polynomial curves fitting points generated with a sine function. The black dotted line is the "true" data, the red line is a first degree polynomial, the green line is second degree, the orange line is third degree and the blue line is fourth degree. The first degree polynomial equation = + is a line with slope a. A line will connect any two ...

  9. Collocation method - Wikipedia

    en.wikipedia.org/wiki/Collocation_method

    In mathematics, a collocation method is a method for the numerical solution of ordinary differential equations, partial differential equations and integral equations.The idea is to choose a finite-dimensional space of candidate solutions (usually polynomials up to a certain degree) and a number of points in the domain (called collocation points), and to select that solution which satisfies the ...