This paper introduces an interpolation framework for the weighted-H2 model
reduction problem. We obtain a new representation of the weighted-H2 norm of
SISO systems that provides new interpolatory first order necessary conditions
for an optimal reduced-order model. The H2 norm representation also provides an
error expression that motivates a new weighted-H2 model reduction algorithm.
Several numerical examples illustrate the effectiveness of the proposed
approach.