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Learning to recognize visual stimuli in neuromorphic VLSI


Corradi, F; Giulioni, M (2012). Learning to recognize visual stimuli in neuromorphic VLSI. In: 2012 IEEE Biomedical Circuits and Systems Conference (BioCAS), Hsinchu, Taiwan, 28 November 2012 - 30 November 2012, 90.

Abstract

We demonstrate learning in a neuromorphic recurrent attractor network distributed onto two VLSI chips. On a monitor we present some stimuli which are input to the network through the neuromorphic retina. Stimulation induces modification in the synaptic weights up to the point in which the selective reverberant states of activity are supported in the absence of stimulus. The network activity and the evolution of the synaptic matrix are monitored during learning. The visitor can draw his/her own stimuli, he/she can modify the learning parameters to teach the network to recognize them.

Abstract

We demonstrate learning in a neuromorphic recurrent attractor network distributed onto two VLSI chips. On a monitor we present some stimuli which are input to the network through the neuromorphic retina. Stimulation induces modification in the synaptic weights up to the point in which the selective reverberant states of activity are supported in the absence of stimulus. The network activity and the evolution of the synaptic matrix are monitored during learning. The visitor can draw his/her own stimuli, he/she can modify the learning parameters to teach the network to recognize them.

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Additional indexing

Item Type:Conference or Workshop Item (Speech), not_refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Event End Date:30 November 2012
Deposited On:03 Sep 2014 12:47
Last Modified:03 Dec 2019 08:04
Publisher:IEEE
Series Name:Biomedical Circuits and Systems Conference (BioCAS)
Number of Pages:1
OA Status:Closed
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1109/BioCAS.2012.6418494

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