A note on quadratic spline interpolation at mid-points

1982 ◽  
Vol 22 (2) ◽  
pp. 261-267 ◽  
Author(s):  
Riaz A. Usmani ◽  
Manabu Sakai
Keyword(s):  
Spline Interpolation ◽  
Quadratic Spline

Quadratic spline interpolation on uniform meshes

1990 ◽  
Vol 30 (3) ◽  
pp. 484-489 ◽  
Author(s):  
M. N. El Tarazi
Keyword(s):  
Spline Interpolation ◽  
Quadratic Spline

C2 Rational Quadratic Spline Interpolation to Monotonic Data

1983 ◽  
Vol 3 (2) ◽  
pp. 141-152 ◽  
Author(s):  
R. DELBOURGO ◽  
J. A. GREGORY
Keyword(s):  
Spline Interpolation ◽  
Quadratic Spline

scholarly journals Integro quadratic spline interpolation

2015 ◽  
Vol 39 (10-11) ◽  
pp. 2973-2980 ◽  
Author(s):  
Jinming Wu ◽  
Xiaolei Zhang
Keyword(s):  
Spline Interpolation ◽  
Quadratic Spline

Quadratic spline interpolation on uniform meshes

1993 ◽  
Vol 11 (5) ◽  
pp. 419-427 ◽  
Author(s):  
S. Sallam ◽  
M.N. El-Tarazi
Keyword(s):  
Spline Interpolation ◽  
Quadratic Spline

scholarly journals Implementation and Performance Evaluation of a Bivariate Cut-HDMR Metamodel for Semiconductor Packaging Design Problems with a Large Number of Input Variables

Materials ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4619
Author(s):  
Yu-Hsiang Yang ◽  
Hsiu-Ping Wei ◽  
Bongtae Han ◽  
Chao Hu
Keyword(s):  
Spline Interpolation ◽  
Absolute Error ◽  
High Dimensional Model Representation ◽  
Quadratic Spline ◽  
Packaging Design ◽  
Sampling Schemes ◽  
Design Variables ◽  
Metamodeling Technique ◽  
Sample Points ◽  
Semiconductor Packaging

A metamodeling technique based on Bivariate Cut High Dimensional Model Representation (Bivariate Cut HDMR) is implemented for a semiconductor packaging design problem with 10 design variables. Bivariate Cut-HDMR constructs a metamodel by considering only up to second-order interactions. The implementation uses three uniformly distributed sample points (s = 3) with quadratic spline interpolation to construct the component functions of Bivariate Cut-HDMR, which can be used to make a direct comparison with a metamodel based on Central Composite Design (CCD). The performance of Bivariate Cut-HDMR is evaluated by two well-known error metrics: R-squared and Relative Average Absolute Error (RAAE). The results are compared with the performance of CCD. Bivariate Cut HDMR does not compromise the accuracy compared to CCD, although the former uses only one-fifth of sample points (201 sample points) required by the latter (1045 sample points). The sampling schemes and the predictions of cut-planes and boundary-planes are discussed to explain possible reasons for the outstanding performance of Bivariate Cut HDMR.

scholarly journals Quadratic spline interpolation

1984 ◽  
Vol 40 (1) ◽  
pp. 66-80 ◽  
Author(s):  
Shenquan Xie
Keyword(s):  
Spline Interpolation ◽  
Quadratic Spline
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