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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...
AIA
2007
15 years 5 months ago
Optimizing number of hidden neurons in neural networks
In this paper, a novel and effective criterion based on the estimation of the signal-to-noise-ratio figure (SNRF) is proposed to optimize the number of hidden neurons in neural ne...
Yue Liu, Janusz A. Starzyk, Zhen Zhu
PRIS
2004
15 years 5 months ago
Character Rotation Absorption Using a Dynamic Neural Network Topology: Comparison With Invariant Features
Abstract. This paper treats on rotation absorption in neural networks for multioriented character recognition. Classical approaches are based on several rotation invariant features...
Christophe Choisy, Hubert Cecotti, Abdel Belaï...