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  2. Function of several real variables - Wikipedia

    en.wikipedia.org/wiki/Function_of_several_real...

    The implicit function theorem of more than two real variables deals with the continuity and differentiability of the function, as follows. [4] Let ϕ(x 1, x 2, …, x n) be a continuous function with continuous first order partial derivatives, and let ϕ evaluated at a point (a, b) = (a 1, a 2, …, a n, b) be zero:

  3. Multivariate interpolation - Wikipedia

    en.wikipedia.org/wiki/Multivariate_interpolation

    In numerical analysis, multivariate interpolation or multidimensional interpolation is interpolation on multivariate functions, having more than one variable or defined over a multi-dimensional domain. [1] A common special case is bivariate interpolation or two-dimensional interpolation, based on two variables or two dimensions.

  4. Lookup table - Wikipedia

    en.wikipedia.org/wiki/Lookup_table

    Functions involving two or more variables require multidimensional array indexing techniques. The latter case may thus employ a two-dimensional array of power[x][y] to replace a function to calculate x y for a limited range of x and y values. Functions that have more than one result may be implemented with lookup tables that are arrays of ...

  5. Bilinear interpolation - Wikipedia

    en.wikipedia.org/wiki/Bilinear_interpolation

    In mathematics, bilinear interpolation is a method for interpolating functions of two variables (e.g., x and y) using repeated linear interpolation. It is usually applied to functions sampled on a 2D rectilinear grid, though it can be generalized to functions defined on the vertices of (a mesh of) arbitrary convex quadrilaterals.

  6. Multilinear polynomial - Wikipedia

    en.wikipedia.org/wiki/Multilinear_polynomial

    The multilinear polynomials in variables form a -dimensional vector space, which is also the basis used in the Fourier analysis of (pseudo-)Boolean functions. Every Boolean function can be uniquely expressed as a multilinear polynomial (up to a choice of domain and codomain).

  7. Multivariate statistics - Wikipedia

    en.wikipedia.org/wiki/Multivariate_statistics

    The extracted variables are known as latent variables or factors; each one may be supposed to account for covariation in a group of observed variables. Canonical correlation analysis finds linear relationships among two sets of variables; it is the generalised (i.e. canonical) version of bivariate [3] correlation.

  8. Radon transform - Wikipedia

    en.wikipedia.org/wiki/Radon_transform

    Radon transform. Maps f on the (x, y)-domain to Rf on the (α, s)-domain.. In mathematics, the Radon transform is the integral transform which takes a function f defined on the plane to a function Rf defined on the (two-dimensional) space of lines in the plane, whose value at a particular line is equal to the line integral of the function over that line.

  9. John's equation - Wikipedia

    en.wikipedia.org/wiki/John's_equation

    John's equation is an ultrahyperbolic partial differential equation satisfied by the X-ray transform of a function. It is named after German-American mathematician Fritz John . Given a function f : R n → R {\displaystyle f\colon \mathbb {R} ^{n}\rightarrow \mathbb {R} } with compact support the X-ray transform is the integral over all lines ...