TY - GEN
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 - 2007
Y1 - 2007
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.
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.
UR - http://www.scopus.com/inward/record.url?scp=49749097134&partnerID=8YFLogxK
U2 - 10.1109/ECCTD.2007.4529721
DO - 10.1109/ECCTD.2007.4529721
M3 - Conference contribution
AN - SCOPUS:49749097134
SN - 1424413427
SN - 9781424413423
T3 - European Conference on Circuit Theory and Design 2007, ECCTD 2007
SP - 815
EP - 818
BT - European Conference on Circuit Theory and Design 2007, ECCTD 2007
PB - IEEE Computer Society
T2 - European Conference on Circuit Theory and Design 2007, ECCTD 2007
Y2 - 26 August 2007 through 30 August 2007
ER -