gradFD for computing gradients and hessians using finite differences

gradFD is a MATLAB/OCTAVE's class which can be used for computing the derivatives and hessians of a function using finite differences. Many schemes have been implemented.

Notice that the hessian computation remains incomplete and needs to be improved.

Features

gradFD is able to

• Compute derivatives with the following schemes
  • forward and backward finite differences of order 1 to 5 (BDx and FDx with x={1,...,5})
  • central finite differences of order 2 to 8 (CDx with x={2,4,6,8})
• Minimize the number of computations (especially the responses at the central points is done only one time)
• Use a specific stepsize in every direction
• Generate the set of sample points which can be used externally for computing responses. These responses can be loaded by the class in order to compute the gradients.