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  2. Multiplicity (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Multiplicity_(mathematics)

    The multiplicity is always finite if the solution is isolated, is perturbation invariant in the sense that a -fold solution becomes a cluster of solutions with a combined multiplicity under perturbation in complex spaces, and is identical to the intersection multiplicity on polynomial systems.

  3. Companion matrix - Wikipedia

    en.wikipedia.org/wiki/Companion_matrix

    Rather, the Jordan canonical form of () contains one Jordan block for each distinct root; if the multiplicity of the root is m, then the block is an m × m matrix with on the diagonal and 1 in the entries just above the diagonal. in this case, V becomes a confluent Vandermonde matrix. [2]

  4. Multiset - Wikipedia

    en.wikipedia.org/wiki/Multiset

    These three multiplicities define three multisets of eigenvalues, which may be all different: Let A be a n × n matrix in Jordan normal form that has a single eigenvalue. Its multiplicity is n, its multiplicity as a root of the minimal polynomial is the size of the largest Jordan block, and its geometric multiplicity is the number of Jordan blocks.

  5. Polynomial greatest common divisor - Wikipedia

    en.wikipedia.org/wiki/Polynomial_greatest_common...

    After computing the GCD of the polynomial and its derivative, further GCD computations provide the complete square-free factorization of the polynomial, which is a factorization = = ⁡ where, for each i, the polynomial f i either is 1 if f does not have any root of multiplicity i or is a square-free polynomial (that is a polynomial without ...

  6. Resolvent cubic - Wikipedia

    en.wikipedia.org/wiki/Resolvent_cubic

    The roots of this polynomial are 0 and the roots of the quadratic polynomial y 2 + 2a 2 y + a 2 2 − 4a 0. If a 2 2 − 4a 0 < 0, then the product of the two roots of this polynomial is smaller than 0 and therefore it has a root greater than 0 (which happens to be −a 2 + 2 √ a 0) and we can take α as the square

  7. Polynomial evaluation - Wikipedia

    en.wikipedia.org/wiki/Polynomial_evaluation

    Horner's method evaluates a polynomial using repeated bracketing: + + + + + = + (+ (+ (+ + (+)))). This method reduces the number of multiplications and additions to just Horner's method is so common that a computer instruction "multiply–accumulate operation" has been added to many computer processors, which allow doing the addition and multiplication operations in one combined step.

  8. Cyclotomic polynomial - Wikipedia

    en.wikipedia.org/wiki/Cyclotomic_polynomial

    The problem of bounding the magnitude of the coefficients of the cyclotomic polynomials has been the object of a number of research papers. [7] If n has at most two distinct odd prime factors, then Migotti showed that the coefficients of are all in the set {1, −1, 0}. [8]

  9. Bézout's theorem - Wikipedia

    en.wikipedia.org/wiki/Bézout's_theorem

    As R is a homogeneous polynomial in two indeterminates, the fundamental theorem of algebra implies that R is a product of pq linear polynomials. If one defines the multiplicity of a common zero of P and Q as the number of occurrences of the corresponding factor in the product, Bézout's theorem is thus proved.