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Fast spline smoothing via spectral factorization concepts

Author(s):

G. De Nicolao, G. Ferrari-Trecate, G. Sparacino
Conference/Journal:

Automatica, vol. 36, no. 11, pp. 1733-1739
Abstract:

When tuning the smoothness parameter of nonparametric regression splines, the evaluation of the so-called degrees of freedom is one of the most computer-intensive tasks. In the paper, a closed-form expression of the degrees of freedom is obtained for the case of cubic splines and equally spaced data when the number of data tends to infinity. State-space methods, Kalman filtering and spectral factorization techniques are used to prove that the asymptotic degrees of freedom are equal to the variance of a suitably defined stationary process. The closed-form expression opens the way to fast spline smoothing algorithms whose computational complexity is about one half of standard methods (or even one fourth under further approximations).

Year:

2000
Type of Publication:

(01)Article
Supervisor:



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% Autogenerated BibTeX entry
@Article { NicFer:2000:IFA_370,
    author={G. De Nicolao and G. Ferrari-Trecate and G. Sparacino},
    title={{Fast spline smoothing via spectral factorization concepts}},
    journal={Automatica},
    year={2000},
    volume={36},
    number={11},
    pages={1733--1739},
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=370}
}
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