  In abstractions of linear dynamic networks, selected node signals are removed
from the network, while keeping the remaining node signals invariant. The
topology and link dynamics, or modules, of an abstracted network will generally
be changed compared to the original network. Abstractions of dynamic networks
can be used to select an appropriate set of node signals that are to be
measured, on the basis of which a particular local module can be estimated. A
method is introduced for network abstraction that generalizes previously
introduced algorithms, as e.g. immersion and the method of indirect inputs. For
this abstraction method it is shown under which conditions on the selected
signals a particular module will remain invariant. This leads to sets of
conditions on selected measured node variables that allow identification of the
target module.
