Login / Signup

Local convexity-preserving C2 rational cubic spline for convex data.

Muhammad AbbasAhmad Abd MajidJamaludin Md Ali
Published in: TheScientificWorldJournal (2014)
We present the smooth and visually pleasant display of 2D data when it is convex, which is contribution towards the improvements over existing methods. This improvement can be used to get the more accurate results. An attempt has been made in order to develop the local convexity-preserving interpolant for convex data using C(2) rational cubic spline. It involves three families of shape parameters in its representation. Data dependent sufficient constraints are imposed on single shape parameter to conserve the inherited shape feature of data. Remaining two of these shape parameters are used for the modification of convex curve to get a visually pleasing curve according to industrial demand. The scheme is tested through several numerical examples, showing that the scheme is local, computationally economical, and visually pleasing.
Keyphrases
  • electronic health record
  • big data
  • data analysis
  • high resolution
  • mass spectrometry
  • risk assessment
  • wastewater treatment
  • deep learning
  • artificial intelligence