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  2. Curve fitting - Wikipedia

    en.wikipedia.org/wiki/Curve_fitting

    With low-order polynomials, the curve is more likely to fall near the midpoint (it's even guaranteed to exactly run through the midpoint on a first degree polynomial). Low-order polynomials tend to be smooth and high order polynomial curves tend to be "lumpy". To define this more precisely, the maximum number of inflection points possible in a ...

  3. Polynomial and rational function modeling - Wikipedia

    en.wikipedia.org/wiki/Polynomial_and_rational...

    A polynomial function is one that has the form = + + + + + where n is a non-negative integer that defines the degree of the polynomial. A polynomial with a degree of 0 is simply a constant function; with a degree of 1 is a line; with a degree of 2 is a quadratic; with a degree of 3 is a cubic, and so on.

  4. hp-FEM - Wikipedia

    en.wikipedia.org/wiki/Hp-FEM

    hp-FEM is a generalization of the finite element method (FEM) for solving partial differential equations numerically based on piecewise-polynomial approximations. hp-FEM originates from the discovery by Barna A. Szabó and Ivo Babuška that the finite element method converges exponentially fast when the mesh is refined using a suitable combination of h-refinements (dividing elements into ...

  5. Extrapolation - Wikipedia

    en.wikipedia.org/wiki/Extrapolation

    The resulting curve can then be extended beyond the end of the known data. Polynomial extrapolation is typically done by means of Lagrange interpolation or using Newton's method of finite differences to create a Newton series that fits the data. The resulting polynomial may be used to extrapolate the data.

  6. Hilbert's sixteenth problem - Wikipedia

    en.wikipedia.org/wiki/Hilbert's_sixteenth_problem

    An investigation of the relative positions of the branches of real algebraic curves of degree n (and similarly for algebraic surfaces). The determination of the upper bound for the number of limit cycles in two-dimensional polynomial vector fields of degree n and an investigation of their relative positions. The first problem is yet unsolved ...

  7. Muller's method - Wikipedia

    en.wikipedia.org/wiki/Muller's_method

    Muller's method fits a parabola, i.e. a second-order polynomial, to the last three obtained points f(x k-1), f(x k-2) and f(x k-3) in each iteration. One can generalize this and fit a polynomial p k,m (x) of degree m to the last m+1 points in the k th iteration. Our parabola y k is written as p k,2 in this notation.

  8. Runge's phenomenon - Wikipedia

    en.wikipedia.org/wiki/Runge's_phenomenon

    A ninth order polynomial interpolation (exact replication of the red curve at 10 points) In the mathematical field of numerical analysis, Runge's phenomenon (German:) is a problem of oscillation at the edges of an interval that occurs when using polynomial interpolation with polynomials of high degree over a set of equispaced interpolation points.

  9. De Casteljau's algorithm - Wikipedia

    en.wikipedia.org/wiki/De_Casteljau's_algorithm

    In the mathematical field of numerical analysis, De Casteljau's algorithm is a recursive method to evaluate polynomials in Bernstein form or Bézier curves, named after its inventor Paul de Casteljau. De Casteljau's algorithm can also be used to split a single Bézier curve into two Bézier curves at an arbitrary parameter value.

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