Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
The saturated attractor analysis, an approach proposed first in [FP] for a comprehensive study of the dynamics of the Linsker model and then successfully applied to the dynamic li...
In this paper we survey work being conducted at Imperial College on the use of machine learning to build Systems Biology models of the effects of toxins on biochemical pathways. Se...
The goal of this paper is to perform a timing optimization of a circuit described by a network of cells on a target structure whose connection delays have discrete values following...
S. A. Senouci, A. Amoura, Helena Krupnova, Gabriel...
Of late, there has been a considerable interest in models, algorithms and methodologies specifically targeted towards designing hardware and software for streaming applications. ...