When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. Diagonalizable matrix - Wikipedia

    en.wikipedia.org/wiki/Diagonalizable_matrix

    The fundamental fact about diagonalizable maps and matrices is expressed by the following: An matrix over a field is diagonalizable if and only if the sum of the dimensions of its eigenspaces is equal to , which is the case if and only if there exists a basis of consisting of eigenvectors of .

  3. 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.

  4. Commuting matrices - Wikipedia

    en.wikipedia.org/wiki/Commuting_matrices

    Two diagonalizable matrices and commute (=) if they are simultaneously diagonalizable (that is, there exists an invertible matrix such that both and are diagonal). [ 4 ] : p. 64 The converse is also true; that is, if two diagonalizable matrices commute, they are simultaneously diagonalizable. [ 5 ]

  5. Jordan normal form - Wikipedia

    en.wikipedia.org/wiki/Jordan_normal_form

    An n × n matrix A is diagonalizable if and only if the sum of the dimensions of the eigenspaces is n. Or, equivalently, if and only if A has n linearly independent eigenvectors. Not all matrices are diagonalizable; matrices that are not diagonalizable are called defective matrices. Consider the following matrix:

  6. Square root of a matrix - Wikipedia

    en.wikipedia.org/wiki/Square_root_of_a_matrix

    An n × n matrix A is diagonalizable if there is a matrix V and a diagonal matrix D such that A = VDV −1. This happens if and only if A has n eigenvectors which constitute a basis for C n. In this case, V can be chosen to be the matrix with the n eigenvectors as columns, and thus a square root of A is = ,

  7. Symmetric matrix - Wikipedia

    en.wikipedia.org/wiki/Symmetric_matrix

    If is diagonalizable it may be decomposed as = where is an orthogonal matrix =, and is a diagonal matrix of the eigenvalues of . In the special case that A {\displaystyle A} is real symmetric, then Q {\displaystyle Q} and Λ {\displaystyle \Lambda } are also real.

  8. Idempotent matrix - Wikipedia

    en.wikipedia.org/wiki/Idempotent_matrix

    An idempotent matrix is always diagonalizable. [3] Its eigenvalues are either 0 or 1: if is a non-zero eigenvector of some idempotent matrix and its associated eigenvalue, then = = = = =, which implies {,}.

  9. Normal matrix - Wikipedia

    en.wikipedia.org/wiki/Normal_matrix

    This is because any function of a non-defective matrix acts directly on each of its eigenvalues, and the conjugate transpose of its spectral decomposition is , where is the diagonal matrix of eigenvalues. Likewise, if two normal matrices commute and are therefore simultaneously diagonalizable, any operation between these matrices also acts on ...