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Title: A new algorithm for computing the smallest eigenvalue of a symmetric positive definite Toeplitz matrix
Authors: Mastronardi, Nicola ×
Laudadio, Teresa
Van Barel, Marc
Vandebril, Raf #
Issue Date: 2008
Conference: International Congress on Computational and Applied Mathematics edition:13 location:Ghent, Belgium date:07-11 July 2008
Abstract: Recent progress in signal processing and estimation has generated considerable interest in the problem of computing the smallest eigenvalue and the corresponding eigenvector of a symmetric positive definite Toeplitz matrix. Some algorithms for computing the latter eigenpair are already described in the literature.
Most of them are based on the Levinson recursion with O(n^2) computational complexity, where n is the order of the Toeplitz matrix.
In this talk we describe a new O(n^2) algorithm for computing the smallest eigenvalue and the corresponding eigenvector of a symmetric positive definite Toeplitz matrix relying on the Levinson algorithm.
Comparisons with existing methods will be shown.
Publication status: published
KU Leuven publication type: IMa
Appears in Collections:Numerical Analysis and Applied Mathematics Section
ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
× corresponding author
# (joint) last author

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