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  2. Taylor series - Wikipedia

    en.wikipedia.org/wiki/Taylor_series

    That is, the Taylor series diverges at x if the distance between x and b is larger than the radius of convergence. The Taylor series can be used to calculate the value of an entire function at every point, if the value of the function, and of all of its derivatives, are known at a single point. Uses of the Taylor series for analytic functions ...

  3. Itô's lemma - Wikipedia

    en.wikipedia.org/wiki/Itô's_lemma

    Memoirs, American Mathematical Society 4, 1–51. Online; Bernt Øksendal (2000). Stochastic Differential Equations. An Introduction with Applications, 5th edition, corrected 2nd printing. Springer. ISBN 3-540-63720-6. Sections 4.1 and 4.2. Philip E Protter (2005). Stochastic Integration and Differential Equations, 2nd edition. Springer.

  4. Taylor dispersion - Wikipedia

    en.wikipedia.org/wiki/Taylor_dispersion

    Taylor dispersion or Taylor diffusion is an apparent or effective diffusion of some scalar field arising on the large scale due to the presence of a strong, confined, zero-mean shear flow on the small scale. Essentially, the shear acts to smear out the concentration distribution in the direction of the flow, enhancing the rate at which it ...

  5. Five-point stencil - Wikipedia

    en.wikipedia.org/wiki/Five-point_stencil

    An illustration of the five-point stencil in one and two dimensions (top, and bottom, respectively). In numerical analysis, given a square grid in one or two dimensions, the five-point stencil of a point in the grid is a stencil made up of the point itself together with its four "neighbors".

  6. Taylor's theorem - Wikipedia

    en.wikipedia.org/wiki/Taylor's_theorem

    Taylor's theorem is named after the mathematician Brook Taylor, who stated a version of it in 1715, [2] although an earlier version of the result was already mentioned in 1671 by James Gregory. [3] Taylor's theorem is taught in introductory-level calculus courses and is one of the central elementary tools in mathematical analysis.

  7. Automatic differentiation - Wikipedia

    en.wikipedia.org/wiki/Automatic_differentiation

    [3] [4] Presently, the two types are highly correlated and complementary and both have a wide variety of applications in, e.g., non-linear optimization, sensitivity analysis, robotics, machine learning, computer graphics, and computer vision. [5] [10] [3] [4] [11] [12] Automatic differentiation is particularly important in the field of machine ...

  8. Numerical differentiation - Wikipedia

    en.wikipedia.org/wiki/Numerical_differentiation

    In fact, all the finite-difference formulae are ill-conditioned [4] and due to cancellation will produce a value of zero if h is small enough. [5] If too large, the calculation of the slope of the secant line will be more accurately calculated, but the estimate of the slope of the tangent by using the secant could be worse. [6]

  9. Total derivative - Wikipedia

    en.wikipedia.org/wiki/Total_derivative

    The rate of change of f with respect to x is usually the partial derivative of f with respect to x; in this case, ∂ f ∂ x = y . {\displaystyle {\frac {\partial f}{\partial x}}=y.} However, if y depends on x , the partial derivative does not give the true rate of change of f as x changes because the partial derivative assumes that y is fixed.