International Congress on Computational and Applied Mathematics edition:13 location:Ghent, Belgium date:07-11 July 2008
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.