• DocumentCode
    2330341
  • Title

    Modified Freeman model: a stability analysis and application to pattern recognition

  • Author

    Ozturk, Mustafa C. ; Xu, Dongming ; Principe, José C.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL, USA
  • Volume
    4
  • fYear
    2004
  • fDate
    25-29 July 2004
  • Firstpage
    3207
  • Abstract
    The biologically realistic Freeman model of the olfactory cortex has been used to solve some engineering problems. However, due to the nature of the nonlinear function in the model, only numerical computer simulations can help explore the behavior of the system for different sets of control parameters. We modify the nonlinear function with a piecewise linear model and show that this simplified model exhibits the same qualitative behavior as the original one. Moreover, for this modified model, we employ the analytical tools of nonlinear dynamics to understand the system response for different parameter values. Finally, similar to the original system, we show that the modified system can be used as an auto-associative memory.
  • Keywords
    biology computing; content-addressable storage; control engineering computing; neurophysiology; nonlinear dynamical systems; pattern recognition; piecewise linear techniques; stability; autoassociative memory; modified Freeman model; nonlinear dynamics; pattern recognition; piecewise linear model; stability analysis; Application software; Biological system modeling; Brain modeling; Computer simulation; Nonlinear control systems; Numerical models; Olfactory; Pattern recognition; Piecewise linear techniques; Stability analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
  • Conference_Location
    Budapest
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-8359-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2004.1381191
  • Filename
    1381191