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 30×30 pixel image in less than 30 μs. Moreover, this platform has been used to realize the visual system of an autonomous mobile robot. © 2007 IEEE.
"Optimized Cellular Neural Network Universal Machine Emulation on FPGA / G. E., Pazienza; J., Bellana Camañes; J., Riera Babures; X., Vilasìs Cardona; M. A., Moreno Armendariz; Balsi, Marco. - STAMPA. - (2007), pp. 815-818. (Intervento presentato al convegno 18th European Conference on Circuit Theory and Design tenutosi a Seville; Spain nel 26-30/8/2007) [10.1109/ECCTD.2007.4529721].
"Optimized Cellular Neural Network Universal Machine Emulation on FPGA
BALSI, Marco
2007
Abstract
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 30×30 pixel image in less than 30 μs. Moreover, this platform has been used to realize the visual system of an autonomous mobile robot. © 2007 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.