Framework for gradient integration by combining radial basis functions method and least-squares method
A framework with a combination of the radial basis functions (RBFs) method and the least-squares integration method is proposed to improve the integration process from gradient to shape. The principle of the framework is described, and the performance of the proposed method is investigated by simula...
Saved in:
Main Authors: | Huang, Lei, Asundi, Anand Krishna |
---|---|
Other Authors: | School of Mechanical and Aerospace Engineering |
Format: | Article |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/101637 http://hdl.handle.net/10220/16536 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Improvement of least squares integration method with iterative compensation for shape reconstruction from gradient
by: Huang, Lei, et al.
Published: (2013) -
Improvement of least-squares integration method with iterative compensations in fringe reflectometry
by: Huang, Lei, et al.
Published: (2013) -
Numerical comparison of least square-based finite-difference (LSFD) and radial basis function-based finite-difference (RBFFD) methods
by: Shu, C., et al.
Published: (2014) -
Orthogonal least-squares learning algorithm with local adaptation process for the radial basis function networks
by: Chng, E.-S., et al.
Published: (2016) -
A least-square radial point collocation method for adaptive analysis in linear elasticity
by: Kee, B.B.T., et al.
Published: (2014)