Corpus ID: 2164193

L1-Optimal Splines for Outlier Rejection

@article{Nagahara2013L1OptimalSF,
  title={L1-Optimal Splines for Outlier Rejection},
  author={Masaaki Nagahara and Clyde F. Martin},
  journal={ArXiv},
  year={2013},
  volume={abs/1308.0384}
}
  • Masaaki Nagahara, Clyde F. Martin
  • Published in ArXiv 2013
  • Mathematics, Computer Science
  • In this article, we consider control theoretic splines with L 1 optimization for rejecting outliers in data. Control theoretic splines are either interpolating or smoothing splines, depending on a cost function with a constraint defined by linear differential equations. Control theoretic splines are effective for Gaussian noise in data since the estimation is based on L 2 optimization. However, in practice, there may be outliers in data, which may occur with vanishingly small probability under… CONTINUE READING

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