T. Bella
University of Rhode Island
17 Papers
115 Citations
T. Bella is an academic researcher from University of Rhode Island. The author has contributed to research in topics: Orthogonal polynomials & Matrix (mathematics). The author has an hindex of 8, co-authored 17 publications. Previous affiliations of T. Bella include University of Connecticut.
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Papers
Computations with quasiseparable polynomials and matrices
TL;DR: The Bjorck-Pereyra algorithm, the Traub algorithm, certain new digital filter structures, as well as QR and divide and conquer eigenvalue algorithms are discussed, to obtain true generalizations of several algorithms.
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A Björck–Pereyra-type algorithm for Szegö–Vandermonde matrices based on properties of unitary Hessenberg matrices
TL;DR: This paper carries over the Bjorck-Pereyra algorithm for solving Vandermonde linear systems to what it is suggested to call Szego-Vandermonde systems where the corresponding polynomial system Φ is the SzEGo polynomials, and shows that for ill-conditioned matrices the new algorithm yields better forward accuracy than Gaussian elimination.
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A Fast Björck-Pereyra-Type Algorithm for Solving Hessenberg-Quasiseparable-Vandermonde Systems
TL;DR: A fast algorithm is derived for solving linear systems where the coefficient matrix is a polynomial-Vandermonde matrix with polynomials defined by a Hessenberg matrix with quasiseparable structure that generalizes the well-known Bjorck-Pereyra algorithm for classical Vandermonde systems involving monomials.
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Classifications of Recurrence Relations via Subclasses of ( H , m )-quasiseparable Matrices
T. Bella,Vadim Olshevsky,Pavel Zhlobich +2 more
- 01 Jan 2011
TL;DR: In this paper, a characterization of polynomials satisfying three-term recurrence relations via tridiagonal matrices and unitary Hessenberg matrices, respectively, is presented.
Lipschitz stability of canonical Jordan bases of H-selfadjoint matrices under structure-preserving perturbations
TL;DR: In this article, the Lipschitz stability of the corresponding affiliation matrices was shown to be robust to small perturbations of invariant subspaces, where the size of a permutation of a subspace is measured using the concepts of a gap and of a semigap.
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