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NGC
2010
Springer
183views Communications» more  NGC 2010»
14 years 11 months ago
Brain-like Computing Based on Distributed Representations and Neurodynamics
A key to overcoming the limitations of classical artificial intelligence and to deal well with enormous amounts of information might be brain-like computing in which distributed re...
Ken Yamane, Masahiko Morita
NN
2007
Springer
131views Neural Networks» more  NN 2007»
15 years 3 months ago
Decoupled echo state networks with lateral inhibition
Building on some prior work, in this paper we describe a novel structure termed the decoupled echo state network (DESN) involving the use of lateral inhibition. Two low-complexity...
Yanbo Xue, Le Yang, Simon Haykin
IJCNN
2006
IEEE
15 years 10 months ago
Global Reinforcement Learning in Neural Networks with Stochastic Synapses
— We have found a more general formulation of the REINFORCE learning principle which had been proposed by R. J. Williams for the case of artificial neural networks with stochast...
Xiaolong Ma, Konstantin Likharev
IJCNN
2006
IEEE
15 years 10 months ago
Training of Large-Scale Feed-Forward Neural Networks
Abstract— Neural processing of large-scale data sets containing both many input / output variables and a large number of training examples often leads to very large networks. Onc...
Udo Seiffert
FPL
2008
Springer
125views Hardware» more  FPL 2008»
15 years 5 months ago
Reconfigurable platforms and the challenges for large-scale implementations of spiking neural networks
FPGA devices have witnessed popularity in their use for the rapid prototyping of biological Spiking Neural Network (SNNs) applications, as they offer the key requirement of reconf...
Jim Harkin, Fearghal Morgan, Steve Hall, Piotr Dud...