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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).
Levinson recursion or Levinson–Durbin recursion is a procedure in linear algebra to recursively calculate the solution to an equation involving a Toeplitz matrix.The algorithm runs in Θ(n 2) time, which is a strong improvement over Gauss–Jordan elimination, which runs in Θ(n 3).
An circulant matrix takes the form = [] or the transpose of this form (by choice of notation). If each is a square matrix, then the matrix is called a block-circulant matrix.. A circulant matrix is fully specified by one vector, , which appears as the first column (or row) of .
This is applied, e.g., in the Kalman filter and recursive least squares methods, to replace the parametric solution, requiring inversion of a state vector sized matrix, with a condition equations based solution. In case of the Kalman filter this matrix has the dimensions of the vector of observations, i.e., as small as 1 in case only one new ...
The Toeplitz Hash Algorithm describes hash functions that compute hash values through matrix multiplication of the key with a suitable Toeplitz matrix. [1] The Toeplitz Hash Algorithm is used in many network interface controllers for receive side scaling. [2] [3] As an example, with the Toeplitz matrix the key results in a hash as follows:
The above discussion shows that the trigonometric moment problem has infinitely many solutions if the Toeplitz matrix is invertible. In that case, the solutions to the problem are in bijective correspondence with minimal unitary extensions of the partial isometry V {\displaystyle V} .
The general Bareiss algorithm is distinct from the Bareiss algorithm for Toeplitz matrices. In some Spanish-speaking countries, this algorithm is also known as Bareiss-Montante, because of René Mario Montante Pardo, a professor of the Universidad Autónoma de Nuevo León, Mexico, who popularized the method among his students.
Sample matrix inversion (or direct matrix inversion) is an algorithm that estimates weights of an array (adaptive filter) by replacing the correlation matrix with its estimate.