Directional derivative

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In mathematics, the directional derivative of a multivariate differentiable function along a given unit vector intuitively represents the rate of change of the function in the direction of that vector. It therefore generalizes the notion of a partial derivative, in which the direction is always taken parallel to of the coordinate axes.

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Definition

The directional derivative of a differentiable function f(\vec{x}) = f(x_1, x_2, \ldots, x_n) along a unit vector \vec{v} = (v_1, \ldots, v_n) is the function defined by the limit

D_{\vec{v}}{f} = \lim_{h \rightarrow 0}{\frac{f(\vec{x} + h\vec{v}) - f(\vec{x})}{h}}

It can be written in terms of the gradient \nabla(f) of f by

D_{\vec{v}}{f} = \nabla(f) \cdot \vec{v}

where \cdot denotes the dot product (Euclidean inner product). At any point p, the directional derivative of f intuitively represents the rate of change in f in the direction of \vec{v} at the point p.

The directional derivative in differential geometry

A vector field at a point p naturally gives rise to linear functionals defined on p by evaluating the directional derivative of a differentiable function f along the unit vector \vec{v}/||\vec{v}|| where \vec{v} is the vector of the tangent space at p assigned by the vector field. The value of the functional is then defined as the value of the corresponding directional derivative at p in the direction of \vec{v}.

Normal derivative

A normal derivative is a directional derivative taken in the direction normal (that is, orthogonal) to some surface in space, or more generally along a unit normal vector field orthogonal to some hypersurface. See for example Neumann boundary condition.

See also

nl:Richtingsafgeleide

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