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Local Convexity Shape-Preserving Data Visualization by Spline Function
Author(s) -
Muhammad Abbas,
Ahmad Abd. Majid,
Mohd Nain Hj Awang,
Jamaludin Md. Ali
Publication year - 2012
Publication title -
isrn mathematical analysis
Language(s) - English
Resource type - Journals
eISSN - 2090-4665
pISSN - 2090-4657
DOI - 10.5402/2012/174048
Subject(s) - convexity , algorithm , computer science , regular polygon , curve fitting , function (biology) , artificial intelligence , mathematics , geometry , machine learning , evolutionary biology , financial economics , economics , biology
The main purpose of this paper is the visualization of convex data that results in a smooth, pleasant, and interactive convexity-preserving curve. The rational cubic function with three free parameters is constructed to preserve the shape of convex data. The free parameters are arranged in a way that two of them are left free for user choice to refine the convex curve as desired, and the remaining one free parameter is constrained to preserve the convexity everywhere. Simple data-dependent constraints are derived on one free parameter, which guarantee to preserve the convexity of curve. Moreover, the scheme under discussion is, 1 flexible, simple, local, and economical as compared to existing schemes. The error bound for the rational cubic function is (ℎ3).

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