  A major problem in system identification is the incorporation of prior
knowledge about the physical properties of the given system, such as stability,
positivity and passivity. In this paper, we present first steps towards
tackling this problem for passive systems. In particular, using ideas from the
theory of reproducing kernel Hilbert spaces, we solve the problem of
identifying a nonnegative input-output operator from data consisting of
input-output trajectories of the system. We prove a representer theorem for
this problem in the case where the input space is finite-dimensional. This
provides a computationally tractable solution, which we show can be obtained by
solving an associated semidefinite program.
