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  2. Crank–Nicolson method - Wikipedia

    en.wikipedia.org/wiki/Crank–Nicolson_method

    The Crank–Nicolson stencil for a 1D problem. The Crank–Nicolson method is based on the trapezoidal rule, giving second-order convergence in time.For linear equations, the trapezoidal rule is equivalent to the implicit midpoint method [citation needed] —the simplest example of a Gauss–Legendre implicit Runge–Kutta method—which also has the property of being a geometric integrator.

  3. Modular multiplicative inverse - Wikipedia

    en.wikipedia.org/wiki/Modular_multiplicative_inverse

    Unlike linear equations over the reals, linear congruences may have zero, one or several solutions. If x is a solution of a linear congruence then every element in x ¯ {\displaystyle {\overline {x}}} is also a solution, so, when speaking of the number of solutions of a linear congruence we are referring to the number of different congruence ...

  4. Horner's method - Wikipedia

    en.wikipedia.org/wiki/Horner's_method

    Horner's method can be used to convert between different positional numeral systems – in which case x is the base of the number system, and the a i coefficients are the digits of the base-x representation of a given number – and can also be used if x is a matrix, in which case the gain in computational efficiency is even greater.

  5. Polynomial interpolation - Wikipedia

    en.wikipedia.org/wiki/Polynomial_interpolation

    For example, given a = f(x) = a 0 x 0 + a 1 x 1 + ··· and b = g(x) = b 0 x 0 + b 1 x 1 + ···, the product ab is a specific value of W(x) = f(x)g(x). One may easily find points along W(x) at small values of x, and interpolation based on those points will yield the terms of W(x) and the specific product ab. As fomulated in Karatsuba ...

  6. Stirling's approximation - Wikipedia

    en.wikipedia.org/wiki/Stirling's_approximation

    Stirling's approximation. Comparison of Stirling's approximation with the factorial. In mathematics, Stirling's approximation (or Stirling's formula) is an asymptotic approximation for factorials. It is a good approximation, leading to accurate results even for small values of .

  7. Lagrange polynomial - Wikipedia

    en.wikipedia.org/wiki/Lagrange_polynomial

    In numerical analysis, the Lagrange interpolating polynomial is the unique polynomial of lowest degree that interpolates a given set of data. Given a data set of coordinate pairs with the are called nodes and the are called values. The Lagrange polynomial has degree and assumes each value at the corresponding node,

  8. Remainder - Wikipedia

    en.wikipedia.org/wiki/Remainder

    For algorithms describing how to calculate the remainder, see division algorithm.) The remainder, as defined above, is called the least positive remainder or simply the remainder . [ 2 ] The integer a is either a multiple of d , or lies in the interval between consecutive multiples of d , namely, q⋅d and ( q + 1) d (for positive q ).

  9. Linear approximation - Wikipedia

    en.wikipedia.org/wiki/Linear_approximation

    Linear approximation. Approximation of a function by its tangent line at a point. Tangent line at (a, f (a)) In mathematics, a linear approximation is an approximation of a general function using a linear function (more precisely, an affine function). They are widely used in the method of finite differences to produce first order methods for ...