Continuous attractor neural networks (CANNs) are emerging as promising models for describing the encoding of continuous stimuli in neural systems. Due to the translational invaria...
We propose an approach for timing analysis of software-based embedded computer systems that builds on the established probabilistic framework of Bayesian networks. We envision an ...
An issue that is equally arising both from social networks and the Semantic Web is the fact that, without the consistent use of the same identifier for an object across systems, i...
Stefano Bortoli, Heiko Stoermer, Paolo Bouquet, Ho...
This paper presents an efficient distributed self-monitoring mechanism for a class of wireless sensor networks used for monitoring and surveillance. In these applications, it is i...
We present a novel approach in characterizing the optimal reliable multi-hop virtual multiple-input single-output (vMISO) routing in ad hoc networks. Under a high node density regi...