Please use this identifier to cite or link to this item: https://doi.org/10.1080/0740817X.2012.726758
Title: Adaptive B-spline knot selection using multi-resolution basis set
Authors: Yuan, Y.
Chen, N. 
Zhou, S.
Keywords: B-splines
free knot splines
knot selection
Lasso
Issue Date: 1-Dec-2013
Source: Yuan, Y., Chen, N., Zhou, S. (2013-12-01). Adaptive B-spline knot selection using multi-resolution basis set. IIE Transactions (Institute of Industrial Engineers) 45 (12) : 1263-1277. ScholarBank@NUS Repository. https://doi.org/10.1080/0740817X.2012.726758
Abstract: B-splines are commonly used to fit complicated functions in Computer Aided Design and signal processing because they are simple yet flexible. However, how to place the knots appropriately in B-spline curve fitting remains a difficult problems. This article discusses a two-stage knot placement method to place knots adapting to the curvature structures of unknown function. In the first stage, a subset of basis functions is selected from the pre-specified multi-resolution basis set using a statistical variable selection method: Lasso. In the second stage, a vector space that is spanned by the selected basis functions is constructed and a concise knot vector is identified that is sufficient to characterize the vector space to fit the unknown function. The effectiveness of the proposed method is demonstrated using numerical studies on multiple representative functions. © 2013 Taylor and Francis Group, LLC.
Source Title: IIE Transactions (Institute of Industrial Engineers)
URI: http://scholarbank.nus.edu.sg/handle/10635/62993
ISSN: 0740817X
DOI: 10.1080/0740817X.2012.726758
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