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EAAI
2006
123views more  EAAI 2006»
15 years 6 months ago
Imitation learning with spiking neural networks and real-world devices
This article is about a new approach in robotic learning systems. It provides a method to use a real-world device that operates in real-time, controlled through a simulated recurr...
Harald Burgsteiner
NPL
2011
14 years 9 months ago
A Neural Network Scheme for Long-Term Forecasting of Chaotic Time Series
The accuracy of a model to forecast a time series diminishes as the prediction horizon increases, in particular when the prediction is carried out recursively. Such decay is faster...
Pilar Gómez-Gil, Juan Manuel Ramírez...
SIAMADS
2010
145views more  SIAMADS 2010»
15 years 26 days ago
Propagation of Spike Sequences in Neural Networks
Precise spatiotemporal sequences of action potentials are observed in many brain areas and are thought to be involved in the neural processing of sensory stimuli. Here, we examine ...
Arnaud Tonnelier
ICASSP
2011
IEEE
14 years 9 months ago
Deep neural networks for acoustic emotion recognition: Raising the benchmarks
Deep Neural Networks (DNNs) denote multilayer artificial neural networks with more than one hidden layer and millions of free parameters. We propose a Generalized Discriminant An...
André Stuhlsatz, Christine Meyer, Florian E...
TNN
2010
121views Management» more  TNN 2010»
15 years 25 days ago
Foundations of implementing the competitive layer model by Lotka-Volterra recurrent neural networks
The competitive layer model (CLM) can be described by an optimization problem. The problem can be further formulated by an energy function, called the CLM energy function, in the s...
Zhang Yi