DocumentCode
83285
Title
Control Theoretic Smoothing Splines
Author
Nagahara, Masaaki ; Martin, Clyde F.
Author_Institution
Grad. Sch. of Inf., Kyoto Univ., Kyoto, Japan
Volume
21
Issue
11
fYear
2014
fDate
Nov. 2014
Firstpage
1394
Lastpage
1397
Abstract
In this letter, we propose control theoretic smoothing splines with L1 optimality for reducing the number of parameters that describes the fitted curve as well as removing outlier data. A control theoretic spline is a smoothing spline that is generated as an output of a given linear dynamical system. Conventional design requires exactly the same number of base functions as given data, and the result is not robust against outliers. To solve these problems, we propose to use L1 optimality, that is, we use the L1 norm for the regularization term and/or the empirical risk term. The optimization is described by a convex optimization, which can be efficiently solved via a numerical optimization software. A numerical example shows the effectiveness of the proposed method.
Keywords
convex programming; curve fitting; signal processing; smoothing methods; splines (mathematics); L1 optimization; control theoretic smoothing splines; convex optimization; fitted curve; linear dynamical system; numerical optimization software; Noise; Optimal control; Optimization; Robustness; Smoothing methods; Software; Splines (mathematics); ${L^1}$ optimization; Control theoretic splines; convex optimization; smoothing splines;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/LSP.2014.2337017
Filename
6849957
Link To Document