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  2. Eigenfunction - Wikipedia

    en.wikipedia.org/wiki/Eigenfunction

    Functions can be written as a linear combination of the basis functions, = = (), for example through a Fourier expansion of f(t). The coefficients b j can be stacked into an n by 1 column vector b = [b 1 b 2 … b n] T. In some special cases, such as the coefficients of the Fourier series of a sinusoidal function, this column vector has finite ...

  3. Eigenvalues and eigenvectors - Wikipedia

    en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors

    For a matrix, eigenvalues and eigenvectors can be used to decompose the matrix—for example by diagonalizing it. Eigenvalues and eigenvectors give rise to many closely related mathematical concepts, and the prefix eigen-is applied liberally when naming them:

  4. 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.

  5. Sturm–Liouville theory - Wikipedia

    en.wikipedia.org/wiki/Sturm–Liouville_theory

    Such values λ are called the eigenvalues of the problem. For each eigenvalue λ, to find the corresponding solution = of the problem. Such functions are called the eigenfunctions associated to each λ. Sturm–Liouville theory is the general study of Sturm–Liouville problems. In particular, for a "regular" Sturm–Liouville problem, it can ...

  6. Eigenvalue algorithm - Wikipedia

    en.wikipedia.org/wiki/Eigenvalue_algorithm

    For example, a projection is a square matrix P satisfying P 2 = P. The roots of the corresponding scalar polynomial equation, λ 2 = λ, are 0 and 1. Thus any projection has 0 and 1 for its eigenvalues. The multiplicity of 0 as an eigenvalue is the nullity of P, while the multiplicity of 1 is the rank of P.

  7. Rayleigh–Ritz method - Wikipedia

    en.wikipedia.org/wiki/Rayleigh–Ritz_method

    That is, the ground-state energy is less than this value. The trial wave-function will always give an expectation value larger than or equal to the ground-energy. If the trial wave function is known to be orthogonal to the ground state, then it will provide a boundary for the energy of some excited state.

  8. Eigenform - Wikipedia

    en.wikipedia.org/wiki/Eigenform

    As the function f is also an eigenvector under each Hecke operator T i, it has a corresponding eigenvalue. More specifically a i, i ≥ 1 turns out to be the eigenvalue of f corresponding to the Hecke operator T i. In the case when f is not a cusp form, the eigenvalues can be given explicitly. [1]

  9. Hilbert–Schmidt theorem - Wikipedia

    en.wikipedia.org/wiki/Hilbert–Schmidt_theorem

    Let (H, , ) be a real or complex Hilbert space and let A : H → H be a bounded, compact, self-adjoint operator.Then there is a sequence of non-zero real eigenvalues λ i, i = 1, …, N, with N equal to the rank of A, such that |λ i | is monotonically non-increasing and, if N = +∞, + =