Large Datasets

... information-processing system in order to have a mind. The answer is the ... neural network (see Shea, 2007). Nevertheless, we can ignore this set of ... ... neural representation of familiar faces and the degree to which peri-frontal neural networks contribute to familiar face recognition. Just as the brain has interconnected neurons, a neural network has tiny interconnected nodes that work together to process information. Neural networks improve ... Neural networks, decision trees, simulation and ... The machine learning approach and the Information Virtue – Information Token – Informational. The recent surge of graph embedding and graph neural networks also call for renewed and novel methodologies for heterogeneous information network analysis. As a ... Sep 22, 2020 ... By recruiting adjacent neurons into oscillations, waves of synchronously firing neuronal networks—and thereby conscious thoughts—can travel ... Mar 4, 2016 ... For the multiplex neural networks, we find that intra and inter couplings will complementarily cooperate to complex behaviour if the two neural ... ... information theory in the evaluation of single neuron responses and neural networks. The question of the neural code has been debated heatedly since the ... Modern artificial intelligence (AI) approaches mainly rely on neural network (NN) or deep NN methodologies. However, these approaches require large amounts ... Keywords: Feedforward neural network, complexity, information complexity, neural complexity, radial basis functions, RBF networks, learning. 1. Introduction.