DocumentCode
1569845
Title
Optimized cellular neural network universal machine emulation on FPGA
Author
Pazienza, Giovanni Egidio ; Bellana-Camañes, Jordi ; Riera-Baburés, Jordi ; Vilasís-Cardona, Xavier ; Moreno-Armendáriz, Marco Antonio ; Balsi, Marco
Author_Institution
Univ. Ramon Llull, Barcelona
fYear
2007
Firstpage
815
Lastpage
818
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 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.
Keywords
cellular neural nets; control engineering computing; field programmable gate arrays; mobile robots; robot vision; FPGA; autonomous mobile robot; cellular neural network; parallel hardware; universal machine emulation; visual system; Cellular neural networks; Cities and towns; Convolution; Emulation; Field programmable gate arrays; Hardware; Pixel; Power system modeling; Turing machines; Visual system;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuit Theory and Design, 2007. ECCTD 2007. 18th European Conference on
Conference_Location
Seville
Print_ISBN
978-1-4244-1341-6
Electronic_ISBN
978-1-4244-1342-3
Type
conf
DOI
10.1109/ECCTD.2007.4529721
Filename
4529721
Link To Document