arXiv:2611.13043v1 Announce Type: new Abstract: This paper explores a controller that is at the crossroads of neuromorphic, i.e., spike-based, and impulsive control systems. The controller consists of a single integrate-and-fire-like neuron that generates an input proportional to the system output when the neuron variable reaches a threshold. We prove that any static output-feedback stabilizable single-input single-output (SISO) linear time-invariant (LTI) plant can be made semi-globally asymptotically stable (sGAS) in closed loop with the proposed neuro-impulsive controller. This improves on existing fixed-amplitude neuromorphic controllers, which only achieve practical stability, but at the price of using graded spiking inputs. Moreover, we provide an algorithm for choosing appropriate controller parameters given a set of admissible initial conditions. A numerical example of an inverted pendulum linearized around its upright equilibrium illustrates the method.