TY - JOUR
T1 - A Mixed Finite Element Discretisation of Thin Plate Splines Based on Biorthogonal Systems
AU - Lamichhane, Bishnu P.
AU - Roberts, Stephen G.
AU - Stals, Linda
N1 - Publisher Copyright:
© 2015, Springer Science+Business Media New York.
PY - 2016/4/1
Y1 - 2016/4/1
N2 - The thin plate spline method is a widely used data fitting technique as it has the ability to smooth noisy data. Here we consider a mixed finite element discretisation of the thin plate spline. By using mixed finite elements the formulation can be defined in-terms of relatively simple stencils, thus resulting in a system that is sparse and whose size only depends linearly on the number of finite element nodes. The mixed formulation is obtained by introducing the gradient of the corresponding function as an additional unknown. The novel approach taken in this paper is to work with a pair of bases for the gradient and the Lagrange multiplier forming a biorthogonal system thus ensuring that the scheme is numerically efficient, and the formulation is stable. Some numerical results are presented to demonstrate the performance of our approach. A preconditioned conjugate gradient method is an efficient solver for the arising linear system of equations.
AB - The thin plate spline method is a widely used data fitting technique as it has the ability to smooth noisy data. Here we consider a mixed finite element discretisation of the thin plate spline. By using mixed finite elements the formulation can be defined in-terms of relatively simple stencils, thus resulting in a system that is sparse and whose size only depends linearly on the number of finite element nodes. The mixed formulation is obtained by introducing the gradient of the corresponding function as an additional unknown. The novel approach taken in this paper is to work with a pair of bases for the gradient and the Lagrange multiplier forming a biorthogonal system thus ensuring that the scheme is numerically efficient, and the formulation is stable. Some numerical results are presented to demonstrate the performance of our approach. A preconditioned conjugate gradient method is an efficient solver for the arising linear system of equations.
KW - Biorthogonal system
KW - Mixed finite element method
KW - Scattered data smoothing
KW - Thin plate splines
UR - http://www.scopus.com/inward/record.url?scp=84961057709&partnerID=8YFLogxK
U2 - 10.1007/s10915-015-0068-6
DO - 10.1007/s10915-015-0068-6
M3 - Article
SN - 0885-7474
VL - 67
SP - 20
EP - 42
JO - Journal of Scientific Computing
JF - Journal of Scientific Computing
IS - 1
ER -