  Gravitational waves generated by the final merger of compact binary systems
depend on the structure of the binary's members. If the binary contains neutron
stars, measuring such waves can teach us about the properties of matter at
extreme densities. Unfortunately, these waves are typically at high frequency
where the sensitivity of broad-band detectors is not good. Learning about dense
matter from these waves will require networks of broad-band detectors combined
with narrow-band detectors that have good sensitivity at high frequencies. This
paper presents an algorithm by which a network can be ``tuned'', in accordance
with the best available information, in order to most effectively measure
merger waves. The algorithm is presented in the context of a toy model that
captures the qualitative features of narrow-band detectors and of certain
binary neutron star merger wave models. By using what is learned from a
sequence of merger measurements, the network can be gradually tuned in order to
accurately measure the waves. The number of measurements needed to reach this
stage depends upon the waves' signal strength, the number of narrow-band
detectors available for the measurement, and the detailed characteristics of
the waves that carry the merger information. Future studies will go beyond this
toy model, encompassing a more realistic description of both the detectors and
the gravitational waves.
