  We introduce the concept of autoregressive moving average (ARMA) filters on a
graph and show how they can be implemented in a distributed fashion. Our graph
filter design philosophy is independent of the particular graph, meaning that
the filter coefficients are derived irrespective of the graph. In contrast to
finite-impulse response (FIR) graph filters, ARMA graph filters are robust
against changes in the signal and/or graph. In addition, when time-varying
signals are considered, we prove that the proposed graph filters behave as ARMA
filters in the graph domain and, depending on the implementation, as first or
higher ARMA filters in the time domain.
