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
Link To Document :
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