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  2. Toeplitz matrix - Wikipedia

    en.wikipedia.org/wiki/Toeplitz_matrix

    An Toeplitz matrix may be defined as a matrix where , =, for constants , …,. The set of n × n {\displaystyle n\times n} Toeplitz matrices is a subspace of the vector space of n × n {\displaystyle n\times n} matrices (under matrix addition and scalar multiplication).

  3. Circulant matrix - Wikipedia

    en.wikipedia.org/wiki/Circulant_matrix

    In linear algebra, a circulant matrix is a square matrix in which all rows are composed of the same elements and each row is rotated one element to the right relative to the preceding row. It is a particular kind of Toeplitz matrix .

  4. List of named matrices - Wikipedia

    en.wikipedia.org/wiki/List_of_named_matrices

    Hurwitz matrix: A matrix whose eigenvalues have strictly negative real part. A stable system of differential equations may be represented by a Hurwitz matrix. M-matrix: A Z-matrix with eigenvalues whose real parts are nonnegative. Positive-definite matrix: A Hermitian matrix with every eigenvalue positive. Stability matrix: Synonym for Hurwitz ...

  5. Szegő limit theorems - Wikipedia

    en.wikipedia.org/wiki/Szegő_limit_theorems

    In mathematical analysis, the Szegő limit theorems describe the asymptotic behaviour of the determinants of large Toeplitz matrices. [1] [2] [3] ... and eigenvalues ...

  6. Tridiagonal matrix - Wikipedia

    en.wikipedia.org/wiki/Tridiagonal_matrix

    As a side note, an unreduced symmetric tridiagonal matrix is a matrix containing non-zero off-diagonal elements of the tridiagonal, where the eigenvalues are distinct while the eigenvectors are unique up to a scale factor and are mutually orthogonal. [19]

  7. Diagonally dominant matrix - Wikipedia

    en.wikipedia.org/wiki/Diagonally_dominant_matrix

    A strictly diagonally dominant matrix (or an irreducibly diagonally dominant matrix [2]) is non-singular. A Hermitian diagonally dominant matrix with real non-negative diagonal entries is positive semidefinite. This follows from the eigenvalues being real, and Gershgorin's circle theorem. If the symmetry requirement is eliminated, such a matrix ...

  8. 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.

  9. Transfer matrix - Wikipedia

    en.wikipedia.org/wiki/Transfer_matrix

    In applied mathematics, the transfer matrix is a formulation in terms of a block-Toeplitz matrix of the two-scale equation, which characterizes refinable functions. Refinable functions play an important role in wavelet theory and finite element theory.