TY - CONF
T1 - Optimized Cellular Neural Network Universal Machine emulation on FPGA
AU - Pazienza, Giovanni Egidio
AU - Bellana-Camañes, Jordi
AU - Riera-Baburés, Jordi
AU - Vilasís-Cardona, Xavier
AU - Moreno-Armendáriz, Marco Antonio
AU - Balsi, Marco
PY - 2008/8/25
Y1 - 2008/8/25
N2 - 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.
AB - 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.
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UR - https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=49749097134&origin=inward
U2 - 10.1109/ECCTD.2007.4529721
DO - 10.1109/ECCTD.2007.4529721
M3 - Paper
SP - 815
EP - 818
T2 - European Conference on Circuit Theory and Design 2007, ECCTD 2007
Y2 - 25 August 2008
ER -