Adaptive synchronization for neutral-type neural networks with stochastic perturbation and Markovian switching parameters.
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 p th moment and almost sure exponential synchronization. Some numerical examples are provided to illustrate the effectiveness and potential of the proposed design techniques.
Wuneng
W
Zhou
Qingyu
Q
Zhu
Peng
P
Shi
Hongye
H
Su
Jian'an
J
Fang
Liuwei
L
Zhou
D000465:Algorithms; D003198:Computer Simulation; D005246:Feedback; D008390:Markov Chains; D015233:Models, Statistical; D016571:Neural Networks, Computer; D013269:Stochastic Processes