Xenofon Koutsoukos

TL;DR: This work presents an approach for dynamic software reconfiguration in sensor networks that utilizes explicit models of the design space of the embedded application and demonstrates the approach using simulation results for a simple sensor network that performs one-dimensional tracking.

TL;DR: In this article, the authors propose a new forward reachability analysis approach to verify safety of cyber-physical systems with reinforcement learning controllers, based on two efficient, exact and over-approximate reachability algorithms for neural network control systems using star sets, which is an efficient representation of polyhedra, using these algorithms, they determine the initial conditions for which a safety-critical system with a neural network controller is safe by incrementally searching a critical initial condition where the safety of the system cannot be established.

TL;DR: In this article, a model based approach to studying degradation phenomena enables combining the physics based modeling of the DC-DC converter with physics of failure models of capacitor degradation, and predict using stochastic simulation methods how system performance deteriorates with time.

TL;DR: It is shown that reachability can be characterized as a viscosity solution of a system of coupled Hamilton-Jacobi-Bellman equations and that this solution converges to the one for the original system as the discretization becomes finer.

TL;DR: This work presents a localization technique that uses the Doppler shift in radio transmission frequency observed by stationary sensors to calculate the position and velocity of the mobile transmitter.