Title :
Adaptive Synchronization for Neutral-Type Neural Networks with Stochastic Perturbation and Markovian Switching Parameters
Author :
Wuneng Zhou ; Qingyu Zhu ; Peng Shi ; Hongye Su ; Jian´an Fang ; Liuwei Zhou
Author_Institution :
Sch. of Inf. Sci. & Technol, Donghua Univ., Shanghai, China
Abstract :
In this paper, the problem of adaptive synchronization is investigated for stochastic neural networks of neutral-type with Markovian switching parameters. Using the M-matrix approach and the stochastic analysis method, some sufficient conditions are obtained to ensure three kinds of adaptive synchronization for the stochastic neutral-type neural networks. These three kinds of adaptive synchronization include the almost sure asymptotical synchronization, exponential synchronization in pth moment and almost sure exponential synchronization. Some numerical examples are provided to illustrate the effectiveness and potential of the proposed design techniques.
Keywords :
Markov processes; control system synthesis; neurocontrollers; perturbation techniques; stochastic systems; synchronisation; time-varying systems; M-matrix approach; Markovian switching parameters; adaptive synchronization; asymptotical synchronization; design techniques; exponential synchronization; stochastic analysis method; stochastic neural networks; stochastic neutral-type neural networks; stochastic perturbation; Adaptive systems; Delays; Neural networks; Stability criteria; Stochastic processes; Switches; Synchronization; $M$ -matrix; Adaptive synchronization; M-matrix; Markovian; Markovian switching; neutral-type neural network; switching;
Journal_Title :
Cybernetics, IEEE Transactions on
DOI :
10.1109/TCYB.2014.2317236
