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» The Recurrent Control Neural Network
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NIPS
2001
14 years 11 months ago
Speech Recognition with Missing Data using Recurrent Neural Nets
In the `missing data' approach to improving the robustness of automatic speech recognition to added noise, an initial process identifies spectraltemporal regions which are do...
S. Parveen, P. Green
IJON
2002
78views more  IJON 2002»
14 years 9 months ago
External termination of recurrent bursting in a model of connected local neural sub-networks
Epileptic seizures are characterized by repetitive synchronous neuronal bursting activity. To study external influences on this activity, a simple model of a chain loop of neurona...
Pawel Kudela, Piotr J. Franaszczuk, Gregory K. Ber...
IJCNN
2006
IEEE
15 years 3 months ago
Backpropagation for Population-Temporal Coded Spiking Neural Networks
Abstract— Supervised learning rules for spiking neural networks are currently only able to use time-to-first-spike coding and are plagued by very irregular learning curves due t...
Benjamin Schrauwen, Jan M. Van Campenhout
IWANN
2001
Springer
15 years 2 months ago
Verifying Properties of Neural Networks
In the beginning of nineties, Hava Siegelmann proposed a new computational model, the Artificial Recurrent Neural Network (ARNN), and proved that it could perform hypercomputation....
Pedro Rodrigues, José Félix Costa, H...
NIPS
1998
14 years 11 months ago
Computational Differences between Asymmetrical and Symmetrical Networks
Symmetrically connected recurrent networks have recently been used as models of a host of neural computations. However, biological neural networks have asymmetrical connections, at...
Zhaoping Li, Peter Dayan