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  2. Factorization of polynomials over finite fields - Wikipedia

    en.wikipedia.org/wiki/Factorization_of...

    The theory of finite fields, whose origins can be traced back to the works of Gauss and Galois, has played a part in various branches of mathematics.Due to the applicability of the concept in other topics of mathematics and sciences like computer science there has been a resurgence of interest in finite fields and this is partly due to important applications in coding theory and cryptography.

  3. Factorization - Wikipedia

    en.wikipedia.org/wiki/Factorization

    The polynomial x 2 + cx + d, where a + b = c and ab = d, can be factorized into (x + a)(x + b).. In mathematics, factorization (or factorisation, see English spelling differences) or factoring consists of writing a number or another mathematical object as a product of several factors, usually smaller or simpler objects of the same kind.

  4. Factorization of polynomials - Wikipedia

    en.wikipedia.org/wiki/Factorization_of_polynomials

    Modern algorithms and computers can quickly factor univariate polynomials of degree more than 1000 having coefficients with thousands of digits. [3] For this purpose, even for factoring over the rational numbers and number fields, a fundamental step is a factorization of a polynomial over a finite field.

  5. Cholesky decomposition - Wikipedia

    en.wikipedia.org/wiki/Cholesky_decomposition

    In Matlab, the chol function gives the Cholesky decomposition. Note that chol uses the upper triangular factor of the input matrix by default, i.e. it computes = where is upper triangular. A flag can be passed to use the lower triangular factor instead. In R, the chol function gives the Cholesky decomposition.

  6. LU decomposition - Wikipedia

    en.wikipedia.org/wiki/LU_decomposition

    Matrix formulae to calculate rows and columns of LU factors by recursion are given in the remaining part of Banachiewicz's paper as Eq. (2.3) and (2.4) (see F90 code example). This paper by Banachiewicz contains both derivation of and factors of respectively non-symmetric and symmetric matrices. They are sometimes confused as later publications ...

  7. Integer factorization - Wikipedia

    en.wikipedia.org/wiki/Integer_factorization

    A general-purpose factoring algorithm, also known as a Category 2, Second Category, or Kraitchik family algorithm, [10] has a running time which depends solely on the size of the integer to be factored. This is the type of algorithm used to factor RSA numbers. Most general-purpose factoring algorithms are based on the congruence of squares method.

  8. Berlekamp's algorithm - Wikipedia

    en.wikipedia.org/wiki/Berlekamp's_algorithm

    In mathematics, particularly computational algebra, Berlekamp's algorithm is a well-known method for factoring polynomials over finite fields (also known as Galois fields). The algorithm consists mainly of matrix reduction and polynomial GCD computations.

  9. Lindsey–Fox algorithm - Wikipedia

    en.wikipedia.org/wiki/Lindsey–Fox_algorithm

    The power of this grid search allows a new polynomial factoring strategy that has proven to be very effective for a certain class of polynomials. This algorithm was conceived of by Pat Lindsey and implemented by Jim Fox in a package of computer programs created to factor high-degree polynomials.