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  2. Johnson's algorithm - Wikipedia

    en.wikipedia.org/wiki/Johnson's_algorithm

    Johnson's algorithm consists of the following steps: [1] [2] First, a new node q is added to the graph, connected by zero-weight edges to each of the other nodes.; Second, the Bellman–Ford algorithm is used, starting from the new vertex q, to find for each vertex v the minimum weight h(v) of a path from q to v.

  3. Zassenhaus algorithm - Wikipedia

    en.wikipedia.org/wiki/Zassenhaus_algorithm

    In mathematics, the Zassenhaus algorithm [1] is a method to calculate a basis for the intersection and sum of two subspaces of a vector space. It is named after Hans Zassenhaus, but no publication of this algorithm by him is known. [2] It is used in computer algebra systems. [3]

  4. Mersenne Twister - Wikipedia

    en.wikipedia.org/wiki/Mersenne_Twister

    The Mersenne Twister is a general-purpose pseudorandom number generator (PRNG) developed in 1997 by Makoto Matsumoto (松本 眞) and Takuji Nishimura (西村 拓士). [1] [2] Its name derives from the choice of a Mersenne prime as its period length. The Mersenne Twister was designed specifically to rectify most of the flaws found in older PRNGs.

  5. Eigenvalue algorithm - Wikipedia

    en.wikipedia.org/wiki/Eigenvalue_algorithm

    Given an n × n square matrix A of real or complex numbers, an eigenvalue λ and its associated generalized eigenvector v are a pair obeying the relation [1] =,where v is a nonzero n × 1 column vector, I is the n × n identity matrix, k is a positive integer, and both λ and v are allowed to be complex even when A is real.l When k = 1, the vector is called simply an eigenvector, and the pair ...

  6. Array programming - Wikipedia

    en.wikipedia.org/wiki/Array_programming

    Function rank is an important concept to array programming languages in general, by analogy to tensor rank in mathematics: functions that operate on data may be classified by the number of dimensions they act on. Ordinary multiplication, for example, is a scalar ranked function because it operates on zero-dimensional data (individual numbers).

  7. Bilinear interpolation - Wikipedia

    en.wikipedia.org/wiki/Bilinear_interpolation

    In mathematics, bilinear interpolation is a method for interpolating functions of two variables (e.g., x and y) using repeated linear interpolation. It is usually applied to functions sampled on a 2D rectilinear grid , though it can be generalized to functions defined on the vertices of (a mesh of) arbitrary convex quadrilaterals .

  8. Inverse iteration - Wikipedia

    en.wikipedia.org/wiki/Inverse_iteration

    Both options have complexity O(n 3), the exact number depends on the chosen method. The choice depends also on the number of iterations. Naively, if at each iteration one solves a linear system, the complexity will be k O ( n 3 ), where k is number of iterations; similarly, calculating the inverse matrix and applying it at each iteration is of ...

  9. Jacobi eigenvalue algorithm - Wikipedia

    en.wikipedia.org/wiki/Jacobi_eigenvalue_algorithm

    Then the indices of the pivot (k, l) must be one of the pairs (,). Also the updating of the index array can be done in O(n) average-case complexity: First, the maximum entry in the updated rows k and l can be found in O(n) steps. In the other rows i, only the entries in columns k and l change.