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  2. 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.

  3. Eigenvalues and eigenvectors - Wikipedia

    en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors

    On the other hand, the geometric multiplicity of the eigenvalue 2 is only 1, because its eigenspace is spanned by just one vector [] and is therefore 1-dimensional. Similarly, the geometric multiplicity of the eigenvalue 3 is 1 because its eigenspace is spanned by just one vector [ 0 0 0 1 ] T {\displaystyle {\begin{bmatrix}0&0&0&1\end{bmatrix ...

  4. 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 ...

  5. Complete set of commuting observables - Wikipedia

    en.wikipedia.org/wiki/Complete_set_of_commuting...

    In quantum mechanics, a complete set of commuting observables (CSCO) is a set of commuting operators whose common eigenvectors can be used as a basis to express any quantum state. In the case of operators with discrete spectra, a CSCO is a set of commuting observables whose simultaneous eigenspaces span the Hilbert space and are linearly ...

  6. Generalized eigenvector - Wikipedia

    en.wikipedia.org/wiki/Generalized_eigenvector

    In linear algebra, a generalized eigenvector of an matrix is a vector which satisfies certain criteria which are more relaxed than those for an (ordinary) eigenvector. [1]Let be an -dimensional vector space and let be the matrix representation of a linear map from to with respect to some ordered basis.

  7. Eigenfunction - Wikipedia

    en.wikipedia.org/wiki/Eigenfunction

    where λ is a scalar. [1] [2] [3] The solutions to Equation may also be subject to boundary conditions.Because of the boundary conditions, the possible values of λ are generally limited, for example to a discrete set λ 1, λ 2, … or to a continuous set over some range.

  8. Companion matrix - Wikipedia

    en.wikipedia.org/wiki/Companion_matrix

    the linear mapping : makes a cyclic []-module, having a basis of the form {,, …,}; or equivalently [] / (()) as []-modules. If the above hold, one says that A is non-derogatory . Not every square matrix is similar to a companion matrix, but every square matrix is similar to a block diagonal matrix made of companion matrices.

  9. Commuting matrices - Wikipedia

    en.wikipedia.org/wiki/Commuting_matrices

    [4]: p. 64 The converse is also true; that is, if two diagonalizable matrices commute, they are simultaneously diagonalizable. [5] But if you take any two matrices that commute (and do not assume they are two diagonalizable matrices) they are simultaneously diagonalizable already if one of the matrices has no multiple eigenvalues. [6]