The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
In this study, we propose the use of specialized influence models to capture the dynamic behavior of a Network-onChip (NoC). Our goal is to construct a versatile modeling framewor...
Abstract-- We consider a one-hop wireless network with independent time varying channels and N users, such as a multiuser uplink or downlink. We first show that general classes of ...
Current proposals for concurrent shared-memory languages, including C++ and C, provide sequential consistency only for programs without data races (the DRF guarantee). While the i...
This paper presents a new functional programming model for graph structures called structured graphs. Structured graphs extend conventional algebraic datatypes with explicit defi...