  Resistive-capacitive (RC) networks are used to model various processes in
engineering, physics or biology. We consider the problem of recovering the
network connection structure from measured input-output data. We address this
problem as a structured identification one, that is, we assume to have a
state-space model of the system (identified with standard techniques, such as
subspace methods) and find a coordinate transformation that puts the identified
system in a form that reveals the nodes connection structure. We characterize
the solution set, that is, the set of all possible RC-networks that can be
associated to the input-output data. We present a possible solution algorithm
and show some computational experiments.
