Considerable effort has been devoted to the development of algorithms for identification of
parsimonious discrete time models from noisy input/output data sets since this facilitates
controller design. Several methods, such as nuclear norm minimization, have been used to
provide approximate solutions to this non-convex problem. However, even though the field
of continuous time system identification is now mature, results on parsimonious model
identification of continuous time systems are still very limited. In this paper, an atomic norm …