• 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