We present an evolutionary methodology that explores the evolution of network topology when a uniform growth of the network traffic is considered. The network redesign problem is ...
The proper functioning of the nervous system depends critically on the intricate network of synaptic connections that are generated during the system development. During the netwo...
Abstract. Spiking Neuron Networks (SNNs) overcome the computational power of neural networks made of thresholds or sigmoidal units. Indeed, SNNs add a new dimension, the temporal a...
Boudjelal Meftah, Olivier Lezoray, Michel Lecluse,...
The way of propagating and control of stochastic signals through Universal Learning Networks (ULNs) and its applications are proposed. ULNs have been already developed to form a s...
Most proposals for quantum neural networks have skipped over the problem of how to train the networks. The mechanics of quantum computing are different enough from classical compu...