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» On the weight dynamics of recurrent learning
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NC
1998
140views Neural Networks» more  NC 1998»
15 years 3 months ago
Recurrent Neural Networks with Iterated Function Systems Dynamics
We suggest a recurrent neural network (RNN) model with a recurrent part corresponding to iterative function systems (IFS) introduced by Barnsley 1] as a fractal image compression ...
Peter Tiño, Georg Dorffner
IJCNN
2006
IEEE
15 years 7 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
157
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TNN
1998
111views more  TNN 1998»
15 years 1 months ago
Modular recurrent neural networks for Mandarin syllable recognition
Abstract—A new modular recurrent neural network (MRNN)based speech-recognition method that can recognize the entire vocabulary of 1280 highly confusable Mandarin syllables is pro...
Sin-Horng Chen, Yuan-Fu Liao
IDEAL
2005
Springer
15 years 7 months ago
Neural Networks: A Replacement for Gaussian Processes?
Abstract. Gaussian processes have been favourably compared to backpropagation neural networks as a tool for regression. We show that a recurrent neural network can implement exact ...
Matthew Lilley, Marcus R. Frean
EAAI
2006
123views more  EAAI 2006»
15 years 1 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