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  2. Gram–Schmidt process - Wikipedia

    en.wikipedia.org/wiki/GramSchmidt_process

    The first two steps of the GramSchmidt process. In mathematics, particularly linear algebra and numerical analysis, the GramSchmidt process or Gram-Schmidt algorithm is a way of finding a set of two or more vectors that are perpendicular to each other.

  3. QR decomposition - Wikipedia

    en.wikipedia.org/wiki/QR_decomposition

    This method has greater numerical stability than the GramSchmidt method above. The following table gives the number of operations in the k -th step of the QR-decomposition by the Householder transformation, assuming a square matrix with size n .

  4. Nonstandard analysis - Wikipedia

    en.wikipedia.org/wiki/Nonstandard_analysis

    For example, any line passing through the point (0, 1) on the y-axis and having infinitesimal slope is parallel to the x-axis. Theorem. For any limited hyperreal r there is a unique standard real denoted st(r) infinitely close to r. The mapping st is a ring homomorphism from the ring of limited hyperreals to R. The mapping st is also external.

  5. Orthogonal matrix - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_matrix

    A GramSchmidt process could orthogonalize the columns, but it is not the most reliable, nor the most efficient, nor the most invariant method. The polar decomposition factors a matrix into a pair, one of which is the unique closest orthogonal matrix to the given matrix, or one of the closest if the given matrix is singular.

  6. List of numerical analysis topics - Wikipedia

    en.wikipedia.org/wiki/List_of_numerical_analysis...

    Hilbert matrix — example of a matrix which is extremely ill-conditioned (and thus difficult to handle) Wilkinson matrix — example of a symmetric tridiagonal matrix with pairs of nearly, but not exactly, equal eigenvalues; Convergent matrix — square matrix whose successive powers approach the zero matrix; Algorithms for matrix multiplication:

  7. Orthogonal polynomials - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_polynomials

    In other words, the sequence is obtained from the sequence of monomials 1, x, x 2, … by the GramSchmidt process with respect to this inner product. Usually the sequence is required to be orthonormal , namely, P n , P n = 1 , {\displaystyle \langle P_{n},P_{n}\rangle =1,} however, other normalisations are sometimes used.

  8. Lenstra–Lenstra–Lovász lattice basis reduction algorithm

    en.wikipedia.org/wiki/Lenstra–Lenstra–Lovász...

    An early successful application of the LLL algorithm was its use by Andrew Odlyzko and Herman te Riele in disproving Mertens conjecture. [5]The LLL algorithm has found numerous other applications in MIMO detection algorithms [6] and cryptanalysis of public-key encryption schemes: knapsack cryptosystems, RSA with particular settings, NTRUEncrypt, and so forth.

  9. Wikipedia : Featured picture candidates/Gram-Schmidt ...

    en.wikipedia.org/wiki/Wikipedia:Featured_picture...

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