Constrained for G1 Cubic Trigonometric Spline Curve Interpolation for Positive Data Set

• Published in: Malaysian Journal of Fundamental and Applied Sciences
• Main Author: Munir N.A.A.A.; Hadi N.A.; Nasir M.A.S.
• Format: Article
• Language: English
• Published: Penerbit UTM Press 2022
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85136163782&doi=10.11113%2fmjfas.v18n3.2353&partnerID=40&md5=7f74756baf93f532396e31bd07d25222

This paper presented the G1 cubic trigonometric spline function with three shape parameters that generate a constrained curve interpolates 2D data. This research ensures that the generated curve passes through all data points in a positive data set yet satisfies the three cases of line constraints given. The three cases are: the data must lie above line L1, the data must lie below line L1, and lastly, the data must lie between two lines L1i and L2i . Simpler schemes with less computation are implemented involving the roles of shape parameters. Two of the shape parameters are set free, while another parameter is fixed to fulfil all the three cases stated. The results show that a smooth curve of the G1 cubic trigonometric spline function can be produced within the constrained line by using the schemes developed while the hereditary shape of the data is preserved. Numerical examples are illustrated and discussed. ©Copyright Munir et al.