Like the derivative of a function in 1d, the gradient of a function on a surface is linear. This means there is a sparse matrix G such that, for a per-vertex function u, Gu is the piecewise constant ...

The cross-gradients joint inversion technique has been applied to multiple geophysical data with a significant improvement on compatibility, but its numerical implementation for practical use is ...

This is a MATLAB demo to elaborate the idea of boundary tracing objects in image using directional gradients In any image the edges lie where the rate of change in the intensity value of the pixel is ...

This paper describes a new algorithm with neuron-by-neuron computation methods for the gradient vector and the Jacobian matrix. The algorithm can handle networks with arbitrarily connected neurons.

Nonnegative matrix factorization (NMF) can be formulated as a minimization problem with bound constraints. Although bound-constrained optimization has been studied extensively in both theory and ...