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EAAI
2006

Imitation learning with spiking neural networks and real-world devices

9 years 7 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 recurrent spiking neural network for robotic experiments. A randomly generated network is used as the main computational unit. Only the weights of the output units of this network are changed during training. It will be shown, that this simple type of a biological realistic spiking neural network
Harald Burgsteiner
Added 12 Dec 2010
Updated 12 Dec 2010
Type Journal
Year 2006
Where EAAI
Authors Harald Burgsteiner
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