• DocumentCode
    1398402
  • Title

    Computation of Synchronized Periodic Solution in a BAM Network With Two Delays

  • Author

    Ge, Juhong ; Xu, Jian

  • Author_Institution
    Sch. of Aerosp. Eng. & Appl. Mech., Tongji Univ., Shanghai, China
  • Volume
    21
  • Issue
    3
  • fYear
    2010
  • fDate
    3/1/2010 12:00:00 AM
  • Firstpage
    439
  • Lastpage
    450
  • Abstract
    A bidirectional associative memory (BAM) neural network with four neurons and two discrete delays is considered to represent an analytical method, namely, perturbation-incremental scheme (PIS). The expressions for the periodic solutions derived from Hopf bifurcation are given by using the PIS. The result shows that the PIS has higher accuracy than the center manifold reduction (CMR) with normal form for the values of time delay not far away from the Hopf bifurcation point. In terms of the PIS, the necessary and sufficient conditions of synchronized periodic solution arising from a Hopf bifurcation are obtained and the synchronized periodic solution is expressed in an analytical form. It can be seen that theoretical analysis is in good agreement with numerical simulation. It implies that the provided method is valid and the obtained result is correct. To the best of our knowledge, the paper is the first one to introduce the PIS to study the periodic solution derived from Hopf bifurcation for a 4-D delayed system quantitatively.
  • Keywords
    bifurcation; content-addressable storage; delays; neural nets; 4D delayed system; Hopf bifurcation point; bidirectional associative memory neural network; center manifold reduction; perturbation-incremental scheme; synchronized periodic solution; time delay; Bidirectional associative memory (BAM) neural network; Hopf bifurcation; periodic solutions; perturbation and incremental scheme; synchronization; time delay; Animals; Computer Simulation; Humans; Information Storage and Retrieval; Models, Neurological; Neural Networks (Computer); Neurons; Pattern Recognition, Automated; Periodicity; Time Factors;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/TNN.2009.2038911
  • Filename
    5401032