- The effectiveness of stochastic power management relies on the accurate system and workload model and effective policy optimization. Workload modeling is a machine learning proce...
We present a parameter inference algorithm for autonomous stochastic linear hybrid systems, which computes a maximum-likelihood model, given only a set of continuous output data of...
This paper is concerned with the problem of receding horizon control of discrete-time systems subject to possibly unbounded random noise inputs, while satisfying hard bounds on the...
This paper proposes the modeling of technical systems and their behavior by means of Unified Modeling Language (UML) State Machines and the extending UML Profile for Schedulabil...
Abstract. In this paper, we study the problem of controlling the expected exit time from a region for a class of stochastic hybrid systems. That is, we find the least costly feedb...