  We propose a method for model reduction on a given frequency range, without
the use of input and output filter weights. The method uses a nonlinear
optimization approach to minimize a frequency limited H2 like cost function.
  An important contribution in the paper is the derivation of the gradient of
the proposed cost function. The fact that we have a closed form expression for
the gradient and that considerations have been taken to make the gradient
computationally efficient to compute enables us to efficiently use
off-the-shelf optimization software to solve the optimization problem.
