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  2. 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 ...

  3. Jacobi eigenvalue algorithm - Wikipedia

    en.wikipedia.org/wiki/Jacobi_eigenvalue_algorithm

    The following algorithm is a description of the Jacobi method in math-like notation. It calculates a vector e which contains the eigenvalues and a matrix E which contains the corresponding eigenvectors; that is, e i {\displaystyle e_{i}} is an eigenvalue and the column E i {\displaystyle E_{i}} an orthonormal eigenvector for e i {\displaystyle ...

  4. Power iteration - Wikipedia

    en.wikipedia.org/wiki/Power_iteration

    #!/usr/bin/env python3 import numpy as np def power_iteration (A, num_iterations: int): # Ideally choose a random vector # To decrease the chance that our vector # Is orthogonal to the eigenvector b_k = np. random. rand (A. shape [1]) for _ in range (num_iterations): # calculate the matrix-by-vector product Ab b_k1 = np. dot (A, b_k) # calculate the norm b_k1_norm = np. linalg. norm (b_k1 ...

  5. Nonlinear eigenproblem - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_eigenproblem

    Françoise Tisseur and Karl Meerbergen, "The quadratic eigenvalue problem," SIAM Review 43 (2), 235–286 (2001) . Gene H. Golub and Henk A. van der Vorst, "Eigenvalue computation in the 20th century," Journal of Computational and Applied Mathematics 123 , 35–65 (2000).

  6. Eigendecomposition of a matrix - Wikipedia

    en.wikipedia.org/wiki/Eigendecomposition_of_a_matrix

    Let A be a square n × n matrix with n linearly independent eigenvectors q i (where i = 1, ..., n).Then A can be factored as = where Q is the square n × n matrix whose i th column is the eigenvector q i of A, and Λ is the diagonal matrix whose diagonal elements are the corresponding eigenvalues, Λ ii = λ i.

  7. Healthy breakfasts could help lower cardiovascular disease risk

    www.aol.com/healthy-breakfasts-could-help-lower...

    For a healthy heart, the best breakfast is one that provides 20% to 30% of daily calorie intake, while wating either less or more may increase certain cardiometabolic risk factors in older adults.

  8. JPMorgan agrees to drop lawsuit against Tesla over stock warrants

    www.aol.com/news/jpmorgan-agrees-drop-lawsuit...

    JPMorgan sued Tesla in November 2021, seeking $162.2 million, alleging that Tesla breached a 2014 contract related to stock warrants it sold to the bank, and which the bank believes became more ...

  9. Divide-and-conquer eigenvalue algorithm - Wikipedia

    en.wikipedia.org/wiki/Divide-and-conquer_eigen...

    In many practical implementations, more complicated rank-1 corrections are used to guarantee stability; some variants even use rank-2 corrections. [ citation needed ] There exist specialized root-finding techniques for rational functions that may do better than the Newton-Raphson method in terms of both performance and stability.