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Fast and accurate Toeplitz matrix triangulation for linear prediction

Authors: null Haesun Park; L. Elden;

Fast and accurate Toeplitz matrix triangulation for linear prediction

Abstract

The authors present a new O(mn) algorithm for triangularizing an m /spl times/ n Toeplitz matrix. The algorithm is based on the previously developed recursive algorithms that exploit the Toeplitz structure and compute each row of the triangular factor via updating and downdating steps. We monitor the conditioning of the downdating problems, and use the method of corrected semi-normal equations to obtain higher accuracy for ill-conditioned downdating problems. Numerical experiments show that the new algorithm improves the accuracy significantly while the computational complexity stays in O(mn). >

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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