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  2. Discrete calculus - Wikipedia

    en.wikipedia.org/wiki/Discrete_calculus

    Meanwhile, calculus, originally called infinitesimal calculus or "the calculus of infinitesimals", is the study of continuous change. Discrete calculus has two entry points, differential calculus and integral calculus. Differential calculus concerns incremental rates of change and the slopes of piece-wise linear curves.

  3. Rate of convergence - Wikipedia

    en.wikipedia.org/wiki/Rate_of_convergence

    Recurrent sequences +:= (), called fixed point iterations, define discrete time autonomous dynamical systems and have important general applications in mathematics through various fixed-point theorems about their convergence behavior.

  4. Second derivative - Wikipedia

    en.wikipedia.org/wiki/Second_derivative

    The second derivative of a function f can be used to determine the concavity of the graph of f. [2] A function whose second derivative is positive is said to be concave up (also referred to as convex), meaning that the tangent line near the point where it touches the function will lie below the graph of the function.

  5. Generalizations of the derivative - Wikipedia

    en.wikipedia.org/wiki/Generalizations_of_the...

    Each entry of this matrix represents a partial derivative, specifying the rate of change of one range coordinate with respect to a change in a domain coordinate. Of course, the Jacobian matrix of the composition g ° f is a product of corresponding Jacobian matrices: J x ( g ° f ) =J ƒ( x ) ( g )J x (ƒ).

  6. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    The rate of convergence is distinguished from the number of iterations required to reach a given accuracy. For example, the function f ( x ) = x 20 − 1 has a root at 1. Since f ′(1) ≠ 0 and f is smooth, it is known that any Newton iteration convergent to 1 will converge quadratically.

  7. Finite difference method - Wikipedia

    en.wikipedia.org/wiki/Finite_difference_method

    To use a finite difference method to approximate the solution to a problem, one must first discretize the problem's domain. This is usually done by dividing the domain into a uniform grid (see image). This means that finite-difference methods produce sets of discrete numerical approximations to the derivative, often in a "time-stepping" manner.

  8. Logistic map - Wikipedia

    en.wikipedia.org/wiki/Logistic_map

    The rate of convergence is linear, except for r = 3, when it is dramatically slow, less than linear (see Bifurcation memory). When the parameter 2 < r < 3, except for the initial values 0 and 1, the fixed point x f 2 = 1 − 1 / r {\displaystyle x_{f2}=1-1/r} is the same as when 1 < r ≤ 2.

  9. Directional derivative - Wikipedia

    en.wikipedia.org/wiki/Directional_derivative

    In multivariable calculus, the directional derivative measures the rate at which a function changes in a particular direction at a given point. [citation needed]The directional derivative of a multivariable differentiable (scalar) function along a given vector v at a given point x intuitively represents the instantaneous rate of change of the function, moving through x with a direction ...