Title :
Mode and Delay-Dependent Adaptive Exponential Synchronization in
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
fDate :
4/1/2012 12:00:00 AM
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;
Journal_Title :
Neural Networks and Learning Systems, IEEE Transactions on
DOI :
10.1109/TNNLS.2011.2179556