gradient of a function

The gradient of a function is called a gradient field.

This term, is curl free as it is the gradient of a function.

Examples include: finding the gradient of a function, integrating the area under a curve, or simply plotting a graph.

Examples of covariant vectors generally appear when taking a gradient of a function.

As one application, we get new estimates for the minimum norm of the gradient of a function of the unit ball.

The adjoint method formulates the gradient of a function towards it's parameters in a constraint optimization form.

By definition, the gradient of a function must satisfy (this definition remains true if ƒ is any tensor)

In mathematics, the structure tensor, also referred to as the second-moment matrix, is a matrix derived from the gradient of a function.

The adjoint state method is a numerical method for efficiently computing the gradient of a function or operator in a numerical optimization problem.

Since the gradient of a function is perpendicular to the contour lines, this is the same as saying that the gradients of 'f' and 'g' are parallel.

An irrotational vector field is locally the gradient of a function, and is therefore orthogonal to the family of level surfaces (the equipotential surfaces).

In mathematics the Laplace operator or Laplacian is a differential operator given by the divergence of the gradient of a function on Euclidean space.

Since not every vector field is the gradient of a function, the problem may or may not have a solution: the necessary and sufficient condition for a smooth vector field V to be the gradient of a function f is that the curl of V must be identically zero.