• DocumentCode
    83285
  • Title

    {L^1} 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