DocumentCode
1816394
Title
Demonstration of the Second Generation Real-Time Cellular Neural Network Processor: RTCNNP-v2
Author
Yildiz, Nerhun ; Cesur, Evren ; Tavsanoglu, Vedat
Author_Institution
Electron. & Commun. Eng. Dept., Yildiz Tech. Univ., Istanbul, Turkey
fYear
2012
fDate
29-31 Aug. 2012
Firstpage
1
Lastpage
2
Abstract
This proceeding is compiled from our previous works, where architecture of the Second-Generation Real-Time Cellular Neural Network (CNN) Processor (RTCNNP-v2) was proposed. The system is designed for applications where high-resolution and high-speed is desired. The structure is fully-pipelined and the processing is real-time. Proposed structure is coded in VHDL and realized on two FPGA devices: one high-end and one low-budget. The system is the only reported CNN implementation supporting real-time Full-HD video image processing, to date.
Keywords
cellular neural nets; field programmable gate arrays; hardware description languages; pipeline processing; video signal processing; FPGA devices; RTCNNP-v2; VHDL; full-HD video image processing; fully-pipelined structure; second generation real-time cellular neural network processor:; Cellular neural networks; Computer architecture; Educational institutions; Field programmable gate arrays; Image resolution; Monitoring; Prototypes;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Nanoscale Networks and Their Applications (CNNA), 2012 13th International Workshop on
Conference_Location
Turin
ISSN
2165-0160
Print_ISBN
978-1-4673-0287-6
Type
conf
DOI
10.1109/CNNA.2012.6331471
Filename
6331471
Link To Document