Please use this identifier to cite or link to this item:
|Title:||A fast modified Newton's method for curvature based denoising of 1D signals||Authors:||Yip, A.M.
|Issue Date:||Aug-2013||Citation:||Yip, A.M., Zhu, W. (2013-08). A fast modified Newton's method for curvature based denoising of 1D signals. Inverse Problems and Imaging 7 (3) : 1075-1097. ScholarBank@NUS Repository. https://doi.org/10.3934/ipi.2013.7.1075||Abstract:||We propose a novel fast numerical method for denoising of 1D signals based on curvature minimization. Motivated by the primal-dual formulation for total variation minimization introduced by Chan, Golub, and Mulet, the proposed method makes use of some auxiliary variables to reformulate the stiff terms presented in the Euler-Lagrange equation which is a fourth-order differential equation. A direct application of Newton's method to the resulting system of equations often fails to converge. We propose a modified Newton's iteration which exhibits local superlinear convergence and global convergence in practical settings. The method is much faster than other existing methods for the model. Unlike all other existing methods, it also does not require tuning any additional parameter besides the model parameter. Numerical experiments are presented to demonstrate the effectiveness of the proposed method. © 2013 American Institute of Mathematical Sciences.||Source Title:||Inverse Problems and Imaging||URI:||http://scholarbank.nus.edu.sg/handle/10635/102642||ISSN:||19308337||DOI:||10.3934/ipi.2013.7.1075|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Apr 5, 2020
WEB OF SCIENCETM
checked on Mar 25, 2020
checked on Mar 28, 2020
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.