453 research outputs found
A Fast Algorithm for the Inversion of Quasiseparable Vandermonde-like Matrices
The results on Vandermonde-like matrices were introduced as a generalization
of polynomial Vandermonde matrices, and the displacement structure of these
matrices was used to derive an inversion formula. In this paper we first
present a fast Gaussian elimination algorithm for the polynomial
Vandermonde-like matrices. Later we use the said algorithm to derive fast
inversion algorithms for quasiseparable, semiseparable and well-free
Vandermonde-like matrices having complexity. To do so we
identify structures of displacement operators in terms of generators and the
recurrence relations(2-term and 3-term) between the columns of the basis
transformation matrices for quasiseparable, semiseparable and well-free
polynomials. Finally we present an algorithm to compute the
inversion of quasiseparable Vandermonde-like matrices
Explicit inverse of a tridiagonal (p,r)-Toeplitz matrix
Peer ReviewedPostprint (author's final draft
On Functions of quasi Toeplitz matrices
Let be a complex valued continuous
function, defined for , such that
. Consider the semi-infinite Toeplitz
matrix associated with the symbol
such that . A quasi-Toeplitz matrix associated with the
continuous symbol is a matrix of the form where
, , and is called a
CQT-matrix. Given a function and a CQT matrix , we provide conditions
under which is well defined and is a CQT matrix. Moreover, we introduce
a parametrization of CQT matrices and algorithms for the computation of .
We treat the case where is assigned in terms of power series and the
case where is defined in terms of a Cauchy integral. This analysis is
applied also to finite matrices which can be written as the sum of a Toeplitz
matrix and of a low rank correction
Efficient cyclic reduction for QBDs with rank structured blocks
We provide effective algorithms for solving block tridiagonal block Toeplitz
systems with quasiseparable blocks, as well as quadratic matrix
equations with quasiseparable coefficients, based on cyclic
reduction and on the technology of rank-structured matrices. The algorithms
rely on the exponential decay of the singular values of the off-diagonal
submatrices generated by cyclic reduction. We provide a formal proof of this
decay in the Markovian framework. The results of the numerical experiments that
we report confirm a significant speed up over the general algorithms, already
starting with the moderately small size
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