Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
We present an evolving neural network model in which synapses appear and disappear stochastically according to bio-inspired probabilities. These are in general nonlinear functions ...
Abstract. Sigmoidal or radial transfer functions do not guarantee the best generalization nor fast learning of neural networks. Families of parameterized transfer functions provide...
— Recently, we have proposed ANSWER: AutoNomouS Wireless sEnsor netwoRk as a service platform whose mission is to provide dependable information services to in-situ mobile users ...
Mohamed F. Younis, Waleed A. Youssef, Mohamed Elto...
Abstract—We describe a neuromorphic chip with a twolayer excitatory-inhibitory recurrent network of spiking neurons that exhibits localized clusters of neural activity. Unlike ot...