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Optimized cellular neural network universal machine emulation on FPGA

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6 Author(s)
Giovanni Egidio Pazienza ; Enginyeria i Arquitectura La Salle, Universitat Ramon Llull, Barcelona, Spain ; Jordi Bellana-Camanes ; Jordi Riera-Babures ; Xavier Vilasis-Cardona
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An FPGA architecture to emulate a single-layer Cellular Neural Network - Universal Machine (CNN-UM) is proposed. It is based on a fast realization of the CNN convolution operation on the parallel hardware of the FPGA. The setup is capable of performing a CNN iteration over a 30 times 30 pixel image in less than 30 mus. Moreover, this platform has been used to realize the visual system of an autonomous mobile robot.

Published in:

Circuit Theory and Design, 2007. ECCTD 2007. 18th European Conference on

Date of Conference:

27-30 Aug. 2007