• Title/Summary/Keyword: Cubic polynomial

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CUBIC FORMULA AND CUBIC CURVES

  • Woo, Sung Sik
    • Communications of the Korean Mathematical Society
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    • v.28 no.2
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    • pp.209-224
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    • 2013
  • The problem of finding rational or integral points of an elliptic curve basically boils down to solving a cubic equation. We look closely at the cubic formula of Cardano to find a criterion for a cubic polynomial to have a rational or integral roots. Also we show that existence of a rational root of a cubic polynomial implies existence of a solution for certain Diophantine equation. As an application we find some integral solutions of some special type for $y^2=x^3+b$.

SOME CUBIC JULIA SETS

  • Lee, Hung-Hwan;Baek, Hun-Ki
    • Journal of applied mathematics & informatics
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    • v.4 no.1
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    • pp.31-38
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    • 1997
  • We figure out geometric properties of the Julia set $J_{\alpha}$ of cubic complex polynomial $C_{\alpha}(z)=z^3 + {\alpha}z(\alpha \epsilon \mathbb{C})$ and the smallest ellipse which surrounds $J_{\alpha}$.

Effect of Improving Accuracy for Effective Atomic number (EAN) and Relative Electron Density (RED) extracted with Polynomial-based Calibration in Dual-energy CT

  • Daehong Kim;Il-Hoon Cho;Mi-jo Lee
    • Journal of the Korean Society of Radiology
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    • v.17 no.7
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    • pp.1017-1023
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    • 2023
  • The purpose of this study was to improve the accuracy of effective atomic number (EAN) and relative electron density (RED) using a polynomial-based calibration method using dual-energy CT images. A phantom composed of 11 tissue-equivalent materials was acquired with dual-energy CT to obtain low- and high-energy images. Using the acquired dual-energy images, the ratio of attenuation of low- and high-energy images for EAN was calibrated based on Stoichiometric, Quadratic, Cubic, Quartic polynomials. EAN and RED were extracted using each calibration method. As a result of the experiment, the average error of EAN using Cubic polynomial-based calibration was minimum. Even in the RED image extracted using EAN, the error of the Cubic polynomial-based RED was minimum. Cubic polynomial-based calibration contributes to improving the accuracy of EAN and RED, and would like to contribute to accurate diagnosis of lesions in CT examinations or quantification of various materials in the human body.

G2 Continuity Smooth Path Planning using Cubic Polynomial Interpolation with Membership Function

  • Chang, Seong-Ryong;Huh, Uk-Youl
    • Journal of Electrical Engineering and Technology
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    • v.10 no.2
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    • pp.676-687
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    • 2015
  • Path planning algorithms are used to allow mobile robots to avoid obstacles and find ways from a start point to a target point. The general path planning algorithm focused on constructing of collision free path. However, a high continuous path can make smooth and efficiently movements. To improve the continuity of the path, the searched waypoints are connected by the proposed polynomial interpolation. The existing polynomial interpolation methods connect two points. In this paper, point groups are created with three points. The point groups have each polynomial. Polynomials are made by matching the differential values and simple matrix calculation. Membership functions are used to distribute the weight of each polynomial at overlapped sections. As a result, the path has $G^2$ continuity. In addition, the proposed method can analyze path numerically to obtain curvature and heading angle. Moreover, it does not require complex calculation and databases to save the created path.

Efficient Piecewise-Cubic Polynomial Curve Approximation Using Uniform Metric

  • Kim, Jae-Hoon
    • Journal of information and communication convergence engineering
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    • v.6 no.3
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    • pp.320-322
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    • 2008
  • We present efficient algorithms for solving the piecewise-cubic approximation problems in the plane. Given a set D of n points in the plane, we find a piecewise-cubic polynomial curve passing through only the points of a subset S of D and approximating the other points using the uniform metric. The goal is to minimize the size of S for a given error tolerance $\varepsilon$, called the min-# problem, or to minimize the error tolerance $\varepsilon$ for a given size of S, called the min-$\varepsilon$ problem. We give algorithms with running times O($n^2$ logn) and O($n^3$) for both problems, respectively.

Development of an Efficient Line Search Method by Using the Sequential Polynomial Approximation (순차적 다항식 근사화를 적용한 효율적 선탐색기법의 개발)

  • 김민수;최동훈
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.19 no.2
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    • pp.433-442
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    • 1995
  • For the line search of a multi-variable optimization, an efficient algorithm is presented. The algorithm sequentially employs several polynomial approximations such as 2-point quadratic interpolation, 3-point cubic interpolation/extrapolation and 4-point cubic interpolation/extrapolation. The order of polynomial function is automatically increased for improving the accuracy of approximation. The method of approximation (interpolation or extrapolation) is automatically switched by checking the slope information of the sample points. Also, for selecting the initial step length along the descent vector, a new approach is presented. The performance of the proposed method is examined by solving typical test problems such as mathematical problems, mechanical design problems and dynamic response problems.

Identification of Fuzzy Systems by means of the Extended GMDH Algorithm

  • Park, Chun-Seong;Park, Jae-Ho;Oh, Sung-Kwun
    • 제어로봇시스템학회:학술대회논문집
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    • 1998.10a
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    • pp.254-259
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    • 1998
  • A new design methology is proposed to identify the structure and parameters of fuzzy model using PNN and a fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Handling), and uses several types of polynomials such as linear, quadratic and cubic besides the biquadratic polynomial used in the GMDH. The FPNN(Fuzzy Polynomial Neural Networks) algorithm uses PNN(Polynomial Neural networks) structure and a fuzzy inference method. In the fuzzy inference method, the simplified and regression polynomial inference methods are used. Here a regression polynomial inference is based on consequence of fuzzy rules with a polynomial equations such as linear, quadratic and cubic equation. Each node of the FPNN is defined as fuzzy rules and its structure is a kind of neuro-fuzzy architecture. In this paper, we will consider a model that combines the advantage of both FPNN and PNN. Also we use the training and testing data set to obtain a balance between the approximation and generalization of process model. Several numerical examples are used to evaluate the performance of the our proposed model.

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A Study on Multi-layer Fuzzy Inference System based on a Modified GMDH Algorithm (수정된 GMDH 알고리즘 기반 다층 퍼지 추론 시스템에 관한 연구)

  • Park, Byoung-Jun;Park, Chun-Seong;Oh, Sung-Kwun
    • Proceedings of the KIEE Conference
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    • 1998.11b
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    • pp.675-677
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    • 1998
  • In this paper, we propose the fuzzy inference algorithm with multi-layer structure. MFIS(Multi-layer Fuzzy Inference System) uses PNN(Polynomial Neural networks) structure and the fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Hendling), and uses several types of polynomials such as linear, quadratic and cubic, as well as the biquadratic polynomial used in the GMDH. In the fuzzy inference method, the simplified and regression polynomial inference methods are used. Here, the regression polynomial inference is based on consequence of fuzzy rules with the polynomial equations such as linear, quadratic and cubic equation. Each node of the MFIS is defined as fuzzy rules and its structure is a kind of neuro-fuzzy structure. We use the training and testing data set to obtain a balance between the approximation and the generalization of process model. Several numerical examples are used to evaluate the performance of the our proposed model.

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APPROXIMATION OF HELIX BY G2 CUBIC POLYNOMIAL CURVES

  • YOUNG JOON AHN
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.28 no.2
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    • pp.59-70
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    • 2024
  • In this paper we present the approximation method of the circular helix by G2 cubic polynomial curves. The approximants are G1 Hermite interpolation of the circular helix and their approximation order is four. We obtain numerical examples to illustrate the geometric continuity and the approximation order of the approximants. The method presented in this paper can be extended to approximating the elliptical helix. Using the property of affine transformation invariance we show that the approximant has G2 continuity and the approximation order four. The numerical examples are also presented to illustrate our assertions.

Development of Learning Materials on Constructibility of Roots of Cubic Polynomials (삼차방정식 해의 작도(불)가능성에 대한 학습 자료 개발)

  • Shin, Hyunyong;Han, Inki
    • Communications of Mathematical Education
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    • v.30 no.4
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    • pp.469-497
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    • 2016
  • In this research, we develop a systematic learning the materials on constructibility of cubic roots. We propose two sets of materials: one is based on concepts of field, vector space, minimal polynomial in abstract algebra, another based on properties of cubic roots in elementary algebra. We assess the validity, applicability, defects and merits of developed materials through prospective teachers, in-service teachers, and professionals. It could be expected that materials be used for advanced secondary students, mathematics majoring college students and mathematics teachers. Furthermore, we may expect the materials be useful for understanding and solving the (un)constructibility problems.