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| Título: | CAVIAR: A 45k neuron, 5M synapse, 12G connects/s AER hardware sensory-processing-learning-actuating system for high-speed visual object recognition and tracking |
Autor: | Serrano-Gotarredona, Teresa CSIC ORCID ; Linares-Barranco, Alejandro CSIC ORCID CVN; Paz-Vicente, R.; Camuñas-Mesa, Luis A. CSIC ORCID; Delbruck, Tobi; Jimenez-Moreno, Gabriel; Civit-Balcells, Antón; Serrano-Gotarredona, Teresa CSIC ORCID ; Acosta, Antonio J. CSIC ORCID; Linares-Barranco, Bernabé CSIC ORCID | Fecha de publicación: | 2009 | Editor: | Institute of Electrical and Electronics Engineers | Citación: | IEEE Transactions on Neural Networks 20(9): 1417-1438 (2009) | Resumen: | 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. © 2009 IEEE. | Descripción: | et al. | Versión del editor: | http://dx.doi.org/10.1109/TNN.2009.2023653 | URI: | http://hdl.handle.net/10261/86527 | DOI: | 10.1109/TNN.2009.2023653 | Identificadores: | doi: 10.1109/TNN.2009.2023653 issn: 1045-9227 e-issn: 1941-0093 |
| Aparece en las colecciones: | (IMSE-CNM) Artículos |
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| Fichero | Descripción | Tamaño | Formato | |
|---|---|---|---|---|
| CAVIAR.pdf | 4,43 MB | Adobe PDF |  Visualizar/Abrir |
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