• DocumentCode
    1431749
  • Title

    Mode and Delay-Dependent Adaptive Exponential Synchronization in p th Moment for Stochastic Delayed Neural Networks With Markovian Switching

  • Author

    Wuneng Zhou ; Dongbing Tong ; Yan Gao ; Chuan Ji ; Hongye Su

  • Author_Institution
    Coll. of Inf. Sci. & Technol., Donghua Univ., Shanghai, China
  • Volume
    23
  • Issue
    4
  • fYear
    2012
  • fDate
    4/1/2012 12:00:00 AM
  • Firstpage
    662
  • Lastpage
    668
  • Abstract
    In this brief, the analysis problem of the mode and delay-dependent adaptive exponential synchronization in th moment is considered for stochastic delayed neural networks with Markovian switching. By utilizing a new nonnegative function and the -matrix approach, several sufficient conditions to ensure the mode and delay-dependent adaptive exponential synchronization in th moment for stochastic delayed neural networks are derived. Via the adaptive feedback control techniques, some suitable parameters update laws are found. To illustrate the effectiveness of the -matrix-based synchronization conditions derived in this brief, a numerical example is provided finally.
  • Keywords
    Markov processes; adaptive control; delays; feedback; matrix algebra; neural nets; stochastic systems; M-matrix-based synchronization conditions; Markovian switching; adaptive feedback control techniques; delay-dependent adaptive exponential synchronization; mode adaptive exponential synchronization; nonnegative function; stochastic delayed neural networks; Adaptive systems; Bismuth; Delay; Neural networks; Stability criteria; Switches; Synchronization; Adaptive exponential synchronization in $p$th moment; Markovian switching; neural networks; stochastic noise; time-varying delays;
  • fLanguage
    English
  • Journal_Title
    Neural Networks and Learning Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    2162-237X
  • Type

    jour

  • DOI
    10.1109/TNNLS.2011.2179556
  • Filename
    6138920