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  2. Buchberger's algorithm - Wikipedia

    en.wikipedia.org/wiki/Buchberger's_algorithm

    A crude version of this algorithm to find a basis for an ideal I of a polynomial ring R proceeds as follows: Input A set of polynomials F that generates I Output A Gröbner basis G for I. G := F; For every f i, f j in G, denote by g i the leading term of f i with respect to the given monomial ordering, and by a ij the least common multiple of g ...

  3. Berlekamp's algorithm - Wikipedia

    en.wikipedia.org/wiki/Berlekamp's_algorithm

    That is, we note that ([] / (())) is a -subspace, and an explicit basis for it can be calculated in the polynomial ring [,] / (,) by computing () and establishing the linear equations on the coefficients of , polynomials that are satisfied iff it is fixed by Frobenius. We note that at this point we have an efficiently computable irreducibility ...

  4. Kernel (linear algebra) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(linear_algebra)

    The left null space of A is the same as the kernel of A T. The left null space of A is the orthogonal complement to the column space of A, and is dual to the cokernel of the associated linear transformation. The kernel, the row space, the column space, and the left null space of A are the four fundamental subspaces associated with the matrix A.

  5. Basis (linear algebra) - Wikipedia

    en.wikipedia.org/wiki/Basis_(linear_algebra)

    The same vector can be represented in two different bases (purple and red arrows). In mathematics, a set B of vectors in a vector space V is called a basis (pl.: bases) if every element of V may be written in a unique way as a finite linear combination of elements of B.

  6. Gröbner basis - Wikipedia

    en.wikipedia.org/wiki/Gröbner_basis

    On the other hand, if all polynomials in the reduced Gröbner basis a homogeneous ideal have a degree of at most D, the Gröbner basis can be computed by linear algebra on the vector space of polynomials of degree less than 2D, which has a dimension (). [1] So, the complexity of this computation is () = ().

  7. 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 ...

  8. 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 ...

  9. Monomial basis - Wikipedia

    en.wikipedia.org/wiki/Monomial_basis

    In mathematics the monomial basis of a polynomial ring is its basis (as a vector space or free module over the field or ring of coefficients) that consists of all monomials.The monomials form a basis because every polynomial may be uniquely written as a finite linear combination of monomials (this is an immediate consequence of the definition of a polynomial).