— This paper presents a fail-safe platform on which cooperative mobile robots rely for their motion. The platform consists of a collision prevention protocol for a dynamic group ...
A neural network model of associative memory is presented which unifies the two historically more relevant enhancements to the basic Little-Hopfield discrete model: the graded resp...
Enrique Carlos Segura Meccia, Roberto P. J. Perazz...
—A major problem in wireless networks is coping with limited resources, such as bandwidth and energy. These issues become a major algorithmic challenge in view of the dynamic nat...
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...