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  2. Tricubic interpolation - Wikipedia

    en.wikipedia.org/wiki/Tricubic_interpolation

    In the mathematical subfield numerical analysis, tricubic interpolation is a method for obtaining values at arbitrary points in 3D space of a function defined on a regular grid. The approach involves approximating the function locally by an expression of the form f ( x , y , z ) = ∑ i = 0 3 ∑ j = 0 3 ∑ k = 0 3 a i j k x i y j z k ...

  3. Injective function - Wikipedia

    en.wikipedia.org/wiki/Injective_function

    The term one-to-one function must not be confused with one-to-one correspondence that refers to bijective functions, which are functions such that each element in the codomain is an image of exactly one element in the domain. A homomorphism between algebraic structures is a function that is compatible with the operations of the structures.

  4. Bijection, injection and surjection - Wikipedia

    en.wikipedia.org/wiki/Bijection,_injection_and...

    A function is injective (one-to-one) if each possible element of the codomain is mapped to by at most one argument. Equivalently, a function is injective if it maps distinct arguments to distinct images. An injective function is an injection. [1] The formal definition is the following.

  5. Bicubic interpolation - Wikipedia

    en.wikipedia.org/wiki/Bicubic_interpolation

    This approach was proposed by Keys, who showed that = produces third-order convergence with respect to the sampling interval of the original function. [1] If we use the matrix notation for the common case =, we can express the equation in a more friendly manner: = [] [] [] for between 0 and 1 for one dimension. Note that for 1-dimensional cubic ...

  6. Trilinear interpolation - Wikipedia

    en.wikipedia.org/wiki/Trilinear_interpolation

    It approximates the value of a function at an intermediate point (,,) within the local axial rectangular prism linearly, using function data on the lattice points. Trilinear interpolation is frequently used in numerical analysis, data analysis, and computer graphics.

  7. Radial basis function interpolation - Wikipedia

    en.wikipedia.org/wiki/Radial_basis_function...

    It has been shown that the resulting interpolation matrix will always be non-singular. This does not violate the Mairhuber–Curtis theorem since the basis functions depend on the points of interpolation. Choosing a radial kernel such that the interpolation matrix is non-singular is exactly the definition of a strictly positive definite function.

  8. Spline interpolation - Wikipedia

    en.wikipedia.org/wiki/Spline_interpolation

    For the elastic rulers being the model for the spline interpolation, one has that to the left of the left-most "knot" and to the right of the right-most "knot" the ruler can move freely and will therefore take the form of a straight line with q′′ = 0.

  9. Marching squares - Wikipedia

    en.wikipedia.org/wiki/Marching_squares

    Typical applications include the contour lines on topographic maps or the generation of isobars for weather maps. Marching squares takes a similar approach to the 3D marching cubes algorithm: Process each cell in the grid independently. Calculate a cell index using comparisons of the contour level(s) with the data values at the cell corners.