In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
TD-FALCON (Temporal Difference - Fusion Architecture for Learning, COgnition, and Navigation) is a class of self-organizing neural networks that incorporates Temporal Difference (...
One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive m...
— We propose a modeling framework based on the event-driven paradigm for populations of neurons which interchange messages. Unlike other strategies our approach is focused on the...
In this paper, we propose a set of dimensioning rules, which deliver high quality sessionbased services over a Next Generation Network based IP/MPLS transport infrastructure. In p...