Abstract. We investigate the computational capabilities of probabilistic cellular automata by means of the density classification problem. We find that a specific probabilistic ...
Background: Reverse engineering cellular networks is currently one of the most challenging problems in systems biology. Dynamic Bayesian networks (DBNs) seem to be particularly su...
Fulvia Ferrazzi, Paola Sebastiani, Marco Ramoni, R...
We have implemented an aspect of learning and memory in the nervous system using analog electronics. Using a simple synaptic circuit we realize networks with Hebbian type adaptati...
Abstract: Since von Neumann's seminal work around 1950, computer scientists and others have studied the algorithms needed to support self-replicating systems. Much of this wor...
A commonly employed measure of the signal amplification properties of an input/output system is its induced L2 norm, sometimes also known as H gain. In general, however, it is ext...