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Memory-efficient Arnoldi algorithms for linearizations of matrix polynomials in Chebyshev basis

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Memory-efficient Arnoldi algorithms for linearizations of matrix polynomials in Chebyshev basis

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Daniel Kressner; Román Moltó, JE. (2014). Memory-efficient Arnoldi algorithms for linearizations of matrix polynomials in Chebyshev basis. Numerical Linear Algebra with Applications. 21(4):569-588. doi:10.1002/nla.1913

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/48638

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Title: Memory-efficient Arnoldi algorithms for linearizations of matrix polynomials in Chebyshev basis
Author: Daniel Kressner Román Moltó, José Enrique
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
Abstract:
Novel memory-efficient Arnoldi algorithms for solving matrix polynomial eigenvalue problems are presented. More specifically, we consider the case of matrix polynomials expressed in the Chebyshev basis, which is often ...[+]
Subjects: Polynomial eigenvalue problems , Linearization , Arnoldi method , Chebyshev basis
Copyrigths: Reserva de todos los derechos
Source:
Numerical Linear Algebra with Applications. (issn: 1070-5325 )
DOI: 10.1002/nla.1913
Publisher:
Wiley
Publisher version: http://dx.doi.org/10.1002/nla.1913
Type: Artículo

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