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  2. Jordan matrix - Wikipedia

    en.wikipedia.org/wiki/Jordan_matrix

    This (n 1 + ⋯ + n r) × (n 1 + ⋯ + n r) square matrix, consisting of r diagonal blocks, can be compactly indicated as ,, or (,, …,,), where the i-th Jordan block is J λ i,n i. For example, the matrix = [] is a 10 × 10 Jordan matrix with a 3 × 3 block with eigenvalue 0, two 2 × 2 blocks with eigenvalue the imaginary unit i, and a 3 × ...

  3. Jordan normal form - Wikipedia

    en.wikipedia.org/wiki/Jordan_normal_form

    Example of a matrix in Jordan normal form. All matrix entries not shown are zero. The outlined squares are known as "Jordan blocks". Each Jordan block contains one number λ i on its main diagonal, and 1s directly above the main diagonal. The λ i s are the eigenvalues of the matrix; they need not be distinct.

  4. Jordan–Chevalley decomposition - Wikipedia

    en.wikipedia.org/wiki/Jordan–Chevalley...

    Let be a field, a finite-dimensional vector space over , and a linear operator over (equivalently, a matrix with entries from ).If the minimal polynomial of splits over (for example if is algebraically closed), then has a Jordan normal form =.

  5. Matrix decomposition - Wikipedia

    en.wikipedia.org/wiki/Matrix_decomposition

    The Jordan normal form and the Jordan–Chevalley decomposition. Applicable to: square matrix A; Comment: the Jordan normal form generalizes the eigendecomposition to cases where there are repeated eigenvalues and cannot be diagonalized, the Jordan–Chevalley decomposition does this without choosing a basis.

  6. Jordan decomposition - Wikipedia

    en.wikipedia.org/wiki/Jordan_decomposition

    In mathematics, Jordan decomposition may refer to Hahn decomposition theorem, and the Jordan decomposition of a measure; Jordan normal form of a matrix; Jordan–Chevalley decomposition of a matrix; Deligne–Lusztig theory, and its Jordan decomposition of a character of a finite group of Lie type

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  8. Row echelon form - Wikipedia

    en.wikipedia.org/wiki/Row_echelon_form

    The reduced row echelon form of a matrix is unique and does not depend on the sequence of elementary row operations used to obtain it. The variant of Gaussian elimination that transforms a matrix to reduced row echelon form is sometimes called Gauss–Jordan elimination. A matrix is in column echelon form if its transpose is in

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