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What is Curve Interpolation

Analyzing Data Through Probabilistic Modeling in Statistics
Computing new and unknown points of a curve and creating a graph of a curve using existing data points – interpolation nodes.
Published in Chapter:
Decision Making and Data Analysis: Curve Modeling via Probabilistic Method
Dariusz Jacek Jakóbczak (Koszalin University of Technology, Poland)
Copyright: © 2021 |Pages: 30
DOI: 10.4018/978-1-7998-4706-9.ch003
Abstract
The proposed method, called probabilistic nodes combination (PNC), is the method of 2D curve modeling and handwriting identification by using the set of key points. Nodes are treated as characteristic points of signature or handwriting for modeling and writer recognition. Identification of handwritten letters or symbols need modeling, and the model of each individual symbol or character is built by a choice of probability distribution function and nodes combination. PNC modeling via nodes combination and parameter γ as probability distribution function enables curve parameterization and interpolation for each specific letter or symbol. Two-dimensional curve is modeled and interpolated via nodes combination and different functions as continuous probability distribution functions: polynomial, sine, cosine, tangent, cotangent, logarithm, exponent, arc sin, arc cos, arc tan, arc cot, or power function.
Full Text Chapter Download: US $37.50 Add to Cart
More Results
Data Analyzing via Probabilistic Modeling: Interpolation and Extrapolation
Computing new and unknown points of a curve and creating a graph of a curve using existing data points – interpolation nodes.
Full Text Chapter Download: US $37.50 Add to Cart
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