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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

 

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Opened Access CAVIAR: A 45k neuron, 5M synapse, 12G connects/s AER hardware sensory-processing-learning-actuating system for high-speed visual object recognition and tracking
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Author: Serrano Gotarredona, Rafael
Oster, Matthias
Lichtsteiner, Patrick
Linares Barranco, Alejandro
Paz Vicente, Rafael
Gómez Rodríguez, Francisco
Camuñas Mesa, Luis Alejandro
Berner, Raphael
Rivas Pérez, Manuel
Jiménez Moreno, Gabriel
Civit-Balcells, Antón
Serrano Gotarredona, María Teresa
Acosta Jiménez, Antonio José
Linares Barranco, Bernabé
Department: Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores
Date: 2009
Published in: IEEE Transactions on Neural Networks, 20 (9), 1417-1438.
Document type: Article
Abstract: 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.
Cite: Serrano Gotarredona, R., Oster, M., Lichtsteiner, P., Linares Barranco, A., Paz Vicente, R., Gómez Rodríguez, F.,...,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.
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Format: PDF

URI: https://hdl.handle.net/11441/75028

DOI: 10.1109/TNN.2009.2023653

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