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  2. Partial fraction decomposition - Wikipedia

    en.wikipedia.org/wiki/Partial_fraction_decomposition

    In algebra, the partial fraction decomposition or partial fraction expansion of a rational fraction (that is, a fraction such that the numerator and the denominator are both polynomials) is an operation that consists of expressing the fraction as a sum of a polynomial (possibly zero) and one or several fractions with a simpler denominator.

  3. Rational root theorem - Wikipedia

    en.wikipedia.org/wiki/Rational_root_theorem

    This shows again that any rational root of P is positive, and the only remaining candidates are 2 and 2\3. To show that 2 is not a root, it suffices to remark that if x = 2 , {\displaystyle x=2,} then 3 x 3 {\displaystyle 3x^{3}} and 5 x − 2 {\displaystyle 5x-2} are multiples of 8 , while − 5 x 2 {\displaystyle -5x^{2}} is not.

  4. Gaussian quadrature - Wikipedia

    en.wikipedia.org/wiki/Gaussian_quadrature

    As the integrand is the third-degree polynomial y(x) = 7x 3 – 8x 2 – 3x + 3, the 2-point Gaussian quadrature rule even returns an exact result. In numerical analysis , an n -point Gaussian quadrature rule , named after Carl Friedrich Gauss , [ 1 ] is a quadrature rule constructed to yield an exact result for polynomials of degree 2 n − 1 ...

  5. Jacobi method - Wikipedia

    en.wikipedia.org/wiki/Jacobi_method

    Input: initial guess x (0) to the solution, (diagonal dominant) matrix A, right-hand side vector b, convergence criterion Output: solution when convergence is reached Comments: pseudocode based on the element-based formula above k = 0 while convergence not reached do for i := 1 step until n do σ = 0 for j := 1 step until n do if j ≠ i then ...

  6. Descartes' rule of signs - Wikipedia

    en.wikipedia.org/wiki/Descartes'_rule_of_signs

    [2] [3] In the 1970s Askold Khovanskii developed the theory of fewnomials that generalises Descartes' rule. [4] The rule of signs can be thought of as stating that the number of real roots of a polynomial is dependent on the polynomial's complexity, and that this complexity is proportional to the number of monomials it has, not its degree.

  7. Polynomial - Wikipedia

    en.wikipedia.org/wiki/Polynomial

    f(x) = a 0 + a 1 x + a 2 x 2 + ⋯ + a n x n, where a n ≠ 0 and n ≥ 2 is a continuous non-linear curve. A non-constant polynomial function tends to infinity when the variable increases indefinitely (in absolute value ).

  8. Gaussian elimination - Wikipedia

    en.wikipedia.org/wiki/Gaussian_elimination

    For example, to solve a system of n equations for n unknowns by performing row operations on the matrix until it is in echelon form, and then solving for each unknown in reverse order, requires n(n + 1)/2 divisions, (2n 3 + 3n 2 − 5n)/6 multiplications, and (2n 3 + 3n 2 − 5n)/6 subtractions, [10] for a total of approximately 2n 3 /3 operations.

  9. Degree of a polynomial - Wikipedia

    en.wikipedia.org/wiki/Degree_of_a_polynomial

    Therefore, let f(x) = g(x) = 2x + 1. Then, f(x)g(x) = 4x 2 + 4x + 1 = 1. Thus deg(f⋅g) = 0 which is not greater than the degrees of f and g (which each had degree 1). Since the norm function is not defined for the zero element of the ring, we consider the degree of the polynomial f(x) = 0 to also be undefined so that it follows the rules of a ...