• DocumentCode
    1717867
  • Title

    Experimental verification of CNN (Cellular Neural Network)-based nonautonomous MLC chaos generator

  • Author

    Kiliç, Recai ; Günay, Enis ; Dalkiran, Fatma Y. ; Mutlu, Ümüt

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Erciyes Univ., Kayseri, Turkey
  • fYear
    2011
  • Firstpage
    624
  • Lastpage
    627
  • Abstract
    In this paper, experimental verification of CNN-based nonautonomous MLC system designed as chaos generator is presented by using programmable and reconfigurable IC technique. The hardware implementation uses FPAA (Field Programmable Analog Array)-based reconfigurable design methodology. FPAA is a programmable IC and a rich variety of systems including analog functions can be realized via dynamic reconfiguration. Experimental results verify the CNN-based MLC chaos generator´s design methodology and that analog hardware solutions using FPAA device can be very effective for real implementation of CNN_based systems.
  • Keywords
    cellular neural nets; chaos generators; field programmable analogue arrays; FPAA; cellular neural network; field programmable analog array; nonautonomous MLC chaos generator; programmable IC technique; reconfigurable IC technique; reconfigurable design methodology; Bifurcation; Chaos; Educational institutions; Field programmable analog arrays; Generators; Hardware; Integrated circuit modeling; Cellular Neural Networks; FPAA (Field Programmable Analog Array); MLC Chaos Generator;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuit Theory and Design (ECCTD), 2011 20th European Conference on
  • Conference_Location
    Linkoping
  • Print_ISBN
    978-1-4577-0617-2
  • Electronic_ISBN
    978-1-4577-0616-5
  • Type

    conf

  • DOI
    10.1109/ECCTD.2011.6043620
  • Filename
    6043620