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  2. Bézier curve - Wikipedia

    en.wikipedia.org/wiki/Bézier_curve

    For quadratic Bézier curves one can construct intermediate points Q 0 and Q 1 such that as t varies from 0 to 1: Point Q 0 (t) varies from P 0 to P 1 and describes a linear Bézier curve. Point Q 1 (t) varies from P 1 to P 2 and describes a linear Bézier curve. Point B(t) is interpolated linearly between Q 0 (t) to Q 1 (t) and describes a ...

  3. Cramer's theorem (algebraic curves) - Wikipedia

    en.wikipedia.org/wiki/Cramer's_theorem_(algebraic...

    If the curve is required to be in a particular sub-category of n-th degree polynomial equations, then fewer than n(n + 3) / 2 points may be necessary and sufficient to determine a unique curve. For example, three (non-collinear) points determine a circle: the generic circle is given by the equation () + = where the center is located at (a, b ...

  4. Algebraic curve - Wikipedia

    en.wikipedia.org/wiki/Algebraic_curve

    An algebraic curve in the Euclidean plane is the set of the points whose coordinates are the solutions of a bivariate polynomial equation p(x, y) = 0.This equation is often called the implicit equation of the curve, in contrast to the curves that are the graph of a function defining explicitly y as a function of x.

  5. Control point (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Control_point_(mathematics)

    For Bézier curves, it has become customary to refer to the ⁠ ⁠-vectors ⁠ ⁠ in a parametric representation of a curve or surface in ⁠ ⁠-space as control points, while the scalar-valued functions ⁠ ⁠, defined over the relevant parameter domain, are the corresponding weight or blending functions.

  6. Linear interpolation - Wikipedia

    en.wikipedia.org/wiki/Linear_interpolation

    Given the two red points, the blue line is the linear interpolant between the points, and the value y at x may be found by linear interpolation. In mathematics, linear interpolation is a method of curve fitting using linear polynomials to construct new data points within the range of a discrete set of known data points.

  7. Gaussian quadrature - Wikipedia

    en.wikipedia.org/wiki/Gaussian_quadrature

    With the n-th polynomial normalized to give P n (1) = 1, the i-th Gauss node, x i, is the i-th root of P n and the weights are given by the formula [3] = [′ ()]. Some low-order quadrature rules are tabulated below (over interval [−1, 1] , see the section below for other intervals).

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    mail.aol.com

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  9. Curve fitting - Wikipedia

    en.wikipedia.org/wiki/Curve_fitting

    A line will connect any two points, so a first degree polynomial equation is an exact fit through any two points with distinct x coordinates. If the order of the equation is increased to a second degree polynomial, the following results: = + +. This will exactly fit a simple curve to three points.