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Snap, [6] or jounce, [2] is the fourth derivative of the position vector with respect to time, or the rate of change of the jerk with respect to time. [4] Equivalently, it is the second derivative of acceleration or the third derivative of velocity, and is defined by any of the following equivalent expressions: = ȷ = = =.
However, this variable can also be made explicit by putting its name as a subscript: if f is a function of a variable x, this is done by writing [6] for the first derivative, for the second derivative, for the third derivative, and
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".
Their algorithm is applicable to higher-order derivatives. A method based on numerical inversion of a complex Laplace transform was developed by Abate and Dubner. [21] An algorithm that can be used without requiring knowledge about the method or the character of the function was developed by Fornberg. [4]
And by your OWN sources admission the names are made up and there are no standards yet. Therefore the title should be something along the lines of "Derivative of Jerk" or "Fourth Derivative of Position" not Jounce which can be misleading. — Preceding unsigned comment added by B787 300 (talk • contribs) 02:35, 12 October 2012 (UTC)
The proof of the general Leibniz rule [2]: 68–69 proceeds by induction. Let and be -times differentiable functions.The base case when = claims that: ′ = ′ + ′, which is the usual product rule and is known to be true.
Special functions: non-elementary functions that have established names and notations due to their importance. Trigonometric functions: relate the angles of a triangle to the lengths of its sides. Nowhere differentiable function called also Weierstrass function: continuous everywhere but not differentiable even at a single point.
The tensor derivative of a vector field (in three dimensions) is a 9-term second-rank tensor – that is, a 3×3 matrix – but can be denoted simply as , where represents the dyadic product. This quantity is equivalent to the transpose of the Jacobian matrix of the vector field with respect to space.