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CAVIAR: A 45k neuron, 5M synapse, 12G connects/s AER hardware sensory-processing-learning-actuating system for high-speed visual object recognition and tracking

AuthorsSerrano-Gotarredona, Teresa ; Linares-Barranco, Alejandro; Paz-Vicente, R.; Camuñas-Mesa, L. ; Delbruck, Tobi; Jimenez-Moreno, Gabriel; Civit-Balcells, Antón; Serrano-Gotarredona, Teresa ; Acosta, Antonio José ; Linares-Barranco, Bernabé
Issue Date2009
PublisherInstitute of Electrical and Electronics Engineers
CitationIEEE Transactions on Neural Networks 20(9): 1417-1438 (2009)
AbstractThis 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. © 2009 IEEE.
Descriptionet al.
Publisher version (URL)http://dx.doi.org/10.1109/TNN.2009.2023653
Identifiersdoi: 10.1109/TNN.2009.2023653
issn: 1045-9227
e-issn: 1941-0093
Appears in Collections:(IMSE-CNM) Artículos
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