• DocumentCode
    324601
  • Title

    Synchronization of hyperchaotic cellular neural networks: a system theory approach

  • Author

    Grassi, Giuseppe ; Mascolo, Saverio

  • Author_Institution
    Dipt. di Math., Lecce Univ., Italy
  • Volume
    2
  • fYear
    1998
  • fDate
    4-9 May 1998
  • Firstpage
    1504
  • Abstract
    In recent years synchronization of chaotic dynamics has received ever increasing attention. Herein, cellular neural networks (CNNs) are considered as a tool for generating hyperchaotic behaviors. By exploiting a system theory approach, a technique for synchronizing a large class of CNNs is developed. In particular, a necessary and sufficient condition for hyperchaos synchronization is given, which is based on the controllability property of linear systems. Finally, in order to show the effectiveness of the proposed technique, the synchronization of a CNN constituted by Chua´s circuits is illustrated
  • Keywords
    cellular neural nets; chaos; controllability; synchronisation; system theory; CNN; Chua circuits; controllability; hyperchaotic cellular neural networks; linear systems; necessary and sufficient condition; synchronization; system theory; Cellular neural networks; Chaotic communication; Controllability; Integrated circuit interconnections; Linear systems; Neurodynamics; Neurons; Pattern formation; State-space methods; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-4859-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.1998.685999
  • Filename
    685999