Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-32048
Serrano-Gotarredona, R; Oster, M; Lichtsteiner, P; Linares-Barranco, A; Paz-Vicente, R; Gomez-Rodriguez, F; Camuñas-Mesa, L; Berner, R; Rivas, M.; Delbruck, T; Liu, S C; Douglas, R J; Hafliger, P; Moreno, G; Civit, A; Serrano-Gotarredona, T; Acosta-Jimenez, A; Linares-Barranco, B (2009). CAVIAR: a 45k neuron, 5M synapse, 12G connects/s AER hardware sensory-processing-learning-actuating system for high-speed visual object recognition and tracking. IEEE Transactions on Neural Networks, 20(9):1417-1438.
This paper describes CAVIAR, a massively parallel hardware implementation of a spike-based sensing-processing-learning-actuating system inspired by the physiology of the nervous system. CAVIAR uses the asychronous address-event representation (AER) communication framework and was developed in the context of a European Union funded project. It has four custom mixed-signal AER chips, five custom digital AER interface components, 45k neurons (spiking cells), up to 5M synapses, performs 12G synaptic operations per second, and achieves millisecond object recognition and tracking latencies.
|Item Type:||Journal Article, refereed, original work|
|Communities & Collections:||07 Faculty of Science > Institute of Neuroinformatics|
|DDC:||570 Life sciences; biology|
|Uncontrolled Keywords:||neuromorphic AER system|
|Deposited On:||06 Mar 2010 16:47|
|Last Modified:||28 Nov 2013 02:51|
|Additional Information:||© 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Related URLs:||http://www.ini.uzh.ch/node/21375 (Organisation)|
|Citations:||Web of Science®. Times cited: 44|
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