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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
IJCNN
2007
IEEE
15 years 8 months ago
The Metro Visualisation of Component Planes for Self-Organising Maps
— The Self-Organising Map is a popular unsupervised neural network model which has successfully been used for clustering various kinds of data. To help in understanding the infl...
Robert Neumayer, Rudolf Mayer, Georg Pölzlbau...
NN
2002
Springer
15 years 1 months ago
Self-organizing maps with recursive neighborhood adaptation
Self-organizing maps (SOMs) are widely used in several fields of application, from neurobiology to multivariate data analysis. In that context, this paper presents variants of the...
John Aldo Lee, Michel Verleysen
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
ICANN
2010
Springer
15 years 2 months ago
Unsupervised Learning of Relations
Learning processes allow the central nervous system to learn relationships between stimuli. Even stimuli from different modalities can easily be associated, and these associations ...
Matthew Cook, Florian Jug, Christoph Krautz, Angel...