• DocumentCode
    1817304
  • Title

    Control chaos in nonautonomous cellular neural networks using impulsive control methods

  • Author

    He, Zhenya ; Zhang, Yifeng ; Yang, Luxi ; Shi, Yuhui

  • Author_Institution
    Dept. of Radio Eng., Southeast Univ., Nanjing, China
  • Volume
    1
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    262
  • Abstract
    Chaotic behavior can be found in nonautonomous cellular neural networks (CNNs). The impulsive control method to control this kind of chaos is used and some satisfactory result are achieved. The condition which ensure existence of periodic solution in the impulse controlled system is provided and proved, and numerical simulation shows the chaos can be eliminated by adding a very small external force. Through observing the time waveform diagram of some controlled periodic orbits, we find the time waveform is very similar to encephalic electric activity or cardiac electric activity in biomedical field study. This illustrate that the nonautonomous CNNs model can successfully model physiological electric response activity signals. Moreover, the physiological explanation is given for the nonautonomous CNNs model
  • Keywords
    bioelectric potentials; cellular neural nets; chaos; electroencephalography; neurophysiology; physiological models; cardiac electric activity; cellular neural networks; chaos; chaotic behavior; encephalic electric activity; impulsive control; physiological model; response activity signals; time waveform; Cellular neural networks; Chaos; Control systems; Feedback control; Force control; Helium; Intelligent networks; Orbits; Proportional control; Radio control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1999. IJCNN '99. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-5529-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.1999.831498
  • Filename
    831498