In this paper, we provide sufficient conditions for dissipativity and local asymptotic stability of discrete-time dynamical systems parametrized by deep neural networks. We leverage the representation networks as pointwise affine maps, thus exposing their linear operators making them accessible to classical system analytic design methods. This allows us “crack open black box” syst...