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  2. 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.

  3. Polynomial interpolation - Wikipedia

    en.wikipedia.org/wiki/Polynomial_interpolation

    One may easily find points along W(x) at small values of x, and interpolation based on those points will yield the terms of W(x) and the specific product ab. As fomulated in Karatsuba multiplication, this technique is substantially faster than quadratic multiplication, even for modest-sized inputs, especially on parallel hardware.

  4. Difference quotient - Wikipedia

    en.wikipedia.org/wiki/Difference_quotient

    The difference between two points, themselves, is known as their Delta (ΔP), as is the difference in their function result, the particular notation being determined by the direction of formation: Forward difference: ΔF(P) = F(P + ΔP) − F(P); Central difference: δF(P) = F(P + ⁠ 1 / 2 ⁠ ΔP) − F(P − ⁠ 1 / 2 ⁠ ΔP);

  5. Euclidean distance - Wikipedia

    en.wikipedia.org/wiki/Euclidean_distance

    The distance between any two points on the real line is the absolute value of the numerical difference of their coordinates, their absolute difference. Thus if p {\displaystyle p} and q {\displaystyle q} are two points on the real line, then the distance between them is given by: [ 1 ]

  6. Euclidean algorithm - Wikipedia

    en.wikipedia.org/wiki/Euclidean_algorithm

    To find the latter, consider two solutions, (x 1, y 1) and (x 2, y 2), where ax 1 + by 1 = c = ax 2 + by 2. or equivalently a(x 1 − x 2) = b(y 2 − y 1). Therefore, the smallest difference between two x solutions is b/g, whereas the smallest difference between two y solutions is a/g. Thus, the solutions may be expressed as x = x 1 − bu/g y ...

  7. Haversine formula - Wikipedia

    en.wikipedia.org/wiki/Haversine_formula

    The haversine formula determines the great-circle distance between two points on a sphere given their longitudes and latitudes.Important in navigation, it is a special case of a more general formula in spherical trigonometry, the law of haversines, that relates the sides and angles of spherical triangles.

  8. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    The simplest method is to use finite difference approximations. A simple two-point estimation is to compute the slope of a nearby secant line through the points (x, f(x)) and (x + h, f(x + h)). [1] Choosing a small number h, h represents a small change in x, and it can be either positive or negative.

  9. Step function - Wikipedia

    en.wikipedia.org/wiki/Step_function

    The Heaviside step function is an often-used step function. A constant function is a trivial example of a step function. Then there is only one interval, =. The sign function sgn(x), which is −1 for negative numbers and +1 for positive numbers, and is the simplest non-constant step function.