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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. Almost ideal demand system - Wikipedia

    en.wikipedia.org/wiki/Almost_ideal_demand_system

    This specification satisfies homogeneity of order 1 in prices, and is a second order approximation of any cost function. From this, demand equations are derived (using Shephard's lemma ), but are however simpler to put in term of budget shares w i = ∂ log ⁡ c ( u , p ) ∂ log ⁡ p i {\displaystyle w_{i}={\frac {\partial \log c(u,p ...

  4. Optimal control - Wikipedia

    en.wikipedia.org/wiki/Optimal_control

    In a direct method, the state or the control, or both, are approximated using an appropriate function approximation (e.g., polynomial approximation or piecewise constant parameterization). Simultaneously, the cost functional is approximated as a cost function. Then, the coefficients of the function approximations are treated as optimization ...

  5. L-reduction - Wikipedia

    en.wikipedia.org/wiki/L-reduction

    Let A and B be optimization problems and c A and c B their respective cost functions. A pair of functions f and g is an L-reduction if all of the following conditions are met: functions f and g are computable in polynomial time, if x is an instance of problem A, then f(x) is an instance of problem B, if y' is a solution to f(x), then g(y' ) is ...

  6. Sigmoid function - Wikipedia

    en.wikipedia.org/wiki/Sigmoid_function

    A wide variety of sigmoid functions including the logistic and hyperbolic tangent functions have been used as the activation function of artificial neurons. Sigmoid curves are also common in statistics as cumulative distribution functions (which go from 0 to 1), such as the integrals of the logistic density , the normal density , and Student's ...

  7. 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 ...

  8. Quadratic assignment problem - Wikipedia

    en.wikipedia.org/wiki/Quadratic_assignment_problem

    Intuitively, the cost function encourages facilities with high flows between each other to be placed close together. The problem statement resembles that of the assignment problem, except that the cost function is expressed in terms of quadratic inequalities, hence the name.

  9. Cost function - Wikipedia

    en.wikipedia.org/wiki/Cost_function

    Cost function. In economics, the cost curve, expressing production costs in terms of the amount produced. In mathematical optimization, ...

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