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2008
Springer
15 years 7 months ago
On the use of spiking neural network for EEG classification
This paper presents a new classification technique of continuous EEG recordings, based on a network of spiking neurons. Human EEG signals published on the BCI Competition website w...
Piyush Goel, Honghai Liu, David J. Brown, Avijit D...
174
Voted
IJON
2000
76views more  IJON 2000»
15 years 7 months ago
Fast neural network simulations with population density methods
The complexity of neural networks of the brain makes studying these networks through computer simulation challenging. Conventional methods, where one models thousands of individua...
Duane Q. Nykamp, Daniel Tranchina
249
Voted
TNN
2010
182views Management» more  TNN 2010»
15 years 2 months ago
A discrete-time neural network for optimization problems with hybrid constraints
Abstract--Recurrent neural networks have become a prominent tool for optimizations including linear or nonlinear variational inequalities and programming, due to its regular mathem...
Huajin Tang, Haizhou Li, Zhang Yi
273
Voted
ICASSP
2011
IEEE
14 years 11 months ago
Extensions of recurrent neural network language model
We present several modifications of the original recurrent neural network language model (RNN LM). While this model has been shown to significantly outperform many competitive l...
Tomas Mikolov, Stefan Kombrink, Lukas Burget, Jan ...
232
Voted
CDC
2008
IEEE
228views Control Systems» more  CDC 2008»
16 years 2 months ago
Stability analysis for neural networks with time-varying delay
— This paper studies the problem of stability analysis for neural networks (NNs) with a time-varying delay. The activation functions are assumed to be neither monotonic, nor diff...
Xun-Lin Zhu, Guang-Hong Yang