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  2. Function approximation - Wikipedia

    en.wikipedia.org/wiki/Function_approximation

    Several progressively more accurate approximations of the step function. An asymmetrical Gaussian function fit to a noisy curve using regression.. In general, a function approximation problem asks us to select a function among a well-defined class [citation needed] [clarification needed] that closely matches ("approximates") a target function [citation needed] in a task-specific way.

  3. Approximation theory - Wikipedia

    en.wikipedia.org/wiki/Approximation_theory

    The objective is to make the approximation as close as possible to the actual function, typically with an accuracy close to that of the underlying computer's floating point arithmetic. This is accomplished by using a polynomial of high degree, and/or narrowing the domain over which the polynomial has to approximate the function. Narrowing the ...

  4. Linearization - Wikipedia

    en.wikipedia.org/wiki/Linearization

    Linearizations of a function are lines—usually lines that can be used for purposes of calculation. Linearization is an effective method for approximating the output of a function = at any = based on the value and slope of the function at =, given that () is differentiable on [,] (or [,]) and that is close to .

  5. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    For this function, it is even the case that Newton's iteration as initialized sufficiently close to 0 or 1 will asymptotically oscillate between these values. For example, Newton's method as initialized at 0.99 yields iterates 0.99, −0.06317, 1.00628, 0.03651, 1.00196, 0.01162, 1.00020, 0.00120, 1.000002, and so on.

  6. Least-squares function approximation - Wikipedia

    en.wikipedia.org/wiki/Least-squares_function...

    In mathematics, least squares function approximation applies the principle of least squares to function approximation, by means of a weighted sum of other functions.The best approximation can be defined as that which minimizes the difference between the original function and the approximation; for a least-squares approach the quality of the approximation is measured in terms of the squared ...

  7. Function cost analysis - Wikipedia

    en.wikipedia.org/wiki/Function_cost_analysis

    Function cost analysis (FСА) (sometimes called function value analysis (FVA)) is a method of technical and economic research of the systems for purpose to optimize a parity between system's (as product or service) consumer functions or properties (also known as value) and expenses to achieve those functions or properties.

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    The search engine that helps you find exactly what you're looking for. Find the most relevant information, video, images, and answers from all across the Web.

  9. Radial basis function - Wikipedia

    en.wikipedia.org/wiki/Radial_basis_function

    A radial function is a function : [,).When paired with a norm on a vector space ‖ ‖: [,), a function of the form = (‖ ‖) is said to be a radial kernel centered at .A radial function and the associated radial kernels are said to be radial basis functions if, for any finite set of nodes {} =, all of the following conditions are true: