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- In mathematics, gradient descent (also often called steepest descent) is a iterative optimization algorithm for finding a local minimum of a differentiable function.
- The derivative of a real differentiable function is a real function.
- For example, a differentiable manifold is a manifold where the change of coordinates from one coordinate map to another is always a differentiable function.
- One of these, Itō's lemma, expresses the composite of an Itō process (or more generally a semimartingale) "dX't" with a twice-differentiable function "f".
- As a differentiable function of a complex variable is equal to its Taylor series (that is, it is analytic), complex analysis is particularly concerned with analytic functions of a complex variable (that is, holomorphic functions).
- In calculus, Taylor's theorem gives an approximation of a "k"-times differentiable function around a given point by a polynomial of degree "k", called the "k"th-order Taylor polynomial.
- By Fermat's theorem, all local maxima and minima of a differentiable function occur at critical points.
- More generally, every sequence of real or complex numbers can appear as coefficients in the Taylor series of an infinitely differentiable function defined on the real line, a consequence of Borel's lemma.
- An important example in calculus is Taylor's theorem, which roughly states that every differentiable function locally looks like a polynomial function, and the Stone–Weierstrass theorem, which states that every continuous function defined on a compact interval of the real axis can be approximated on the whole interval as closely as desired by a polynomial function.
- The basic way to maximize a differentiable function is to find the stationary points (the points where the derivative is zero); since the derivative of a sum is just the sum of the derivatives, but the derivative of a product requires the product rule, it is easier to compute the stationary points of the log-likelihood of independent events than for the likelihood of independent events.
- Any differentiable function may be used for [...]. The examples that follow use a variety of elementary functions; special functions may also be used.
- Because a differentiable functional is stationary at its local extrema, the Euler–Lagrange equation is useful for solving optimization problems in which, given some functional, one seeks the function minimizing or maximizing it.
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