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SYNASC
2005
IEEE
97views Algorithms» more  SYNASC 2005»
15 years 9 months ago
A Reinforcement Learning Algorithm for Spiking Neural Networks
The paper presents a new reinforcement learning mechanism for spiking neural networks. The algorithm is derived for networks of stochastic integrate-and-fire neurons, but it can ...
Razvan V. Florian
BC
2005
98views more  BC 2005»
15 years 4 months ago
Integrating behavioral and neural data in a model of zebrafish network interaction
The spinal neural networks of larval zebrafish (Danio rerio) generate a variety of movements such as escape, struggling, and swimming. Various mechanisms at the neural and network ...
P. Dwight Kuo, Chris Eliasmith
ANNPR
2008
Springer
15 years 6 months ago
Supervised Incremental Learning with the Fuzzy ARTMAP Neural Network
Abstract. Automatic pattern classifiers that allow for on-line incremental learning can adapt internal class models efficiently in response to new information without retraining fr...
Jean-François Connolly, Eric Granger, Rober...
ANNPR
2006
Springer
15 years 6 months ago
A Convolutional Neural Network Tolerant of Synaptic Faults for Low-Power Analog Hardware
Abstract. Recently, the authors described a training method for a convolutional neural network of threshold neurons. Hidden layers are trained by by clustering, in a feed-forward m...
Johannes Fieres, Karlheinz Meier, Johannes Schemme...
EAAI
2006
157views more  EAAI 2006»
15 years 4 months ago
Blind source separation based on self-organizing neural network
This contribution describes a neural network that self-organizes to recover the underlying original sources from typical sensor signals. No particular information is required abou...
Anke Meyer-Bäse, Peter Gruber, Fabian J. Thei...