Probabilistic 2D Point Interpolation and Extrapolation via Data Modeling
Abstract
Mathematics and computer science are interested in methods of 2D curve interpolation and
extrapolation using the set of key points (knots). A proposed method of Hurwitz- Radon Matrices (MHR)
is such a method. This novel method is based on the family of Hurwitz-Radon (HR) matrices which
possess columns composed of orthogonal vectors. Two-dimensional curve is interpolated via different
functions as probability distribution functions: polynomial, sinus, cosine, tangent, cotangent, logarithm,
exponent, arcsin, arccos, arctan, arcctg or power function, also inverse functions. It is shown how to
build the orthogonal matrix operator and how to use it in a process of curve reconstruction.
extrapolation using the set of key points (knots). A proposed method of Hurwitz- Radon Matrices (MHR)
is such a method. This novel method is based on the family of Hurwitz-Radon (HR) matrices which
possess columns composed of orthogonal vectors. Two-dimensional curve is interpolated via different
functions as probability distribution functions: polynomial, sinus, cosine, tangent, cotangent, logarithm,
exponent, arcsin, arccos, arctan, arcctg or power function, also inverse functions. It is shown how to
build the orthogonal matrix operator and how to use it in a process of curve reconstruction.
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