Stability analysis for discrete delayed Markovian jumping neural networks with partly unknown transition probabilities

2011 ◽  
Vol 74 (18) ◽  
pp. 3768-3772 ◽  
Author(s):  
Y. Lu ◽  
W. Ren ◽  
S. Yi ◽  
Y. Zuo
Keyword(s):  
Neural Networks ◽  
Stability Analysis ◽  
Transition Probabilities ◽  
Markovian Jumping ◽  
Partly Unknown Transition Probabilities

scholarly journals Finite-Time Boundedness for a Class of Delayed Markovian Jumping Neural Networks with Partly Unknown Transition Probabilities

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Li Liang
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Transition Probabilities ◽  
The State ◽  
Time Interval ◽  
Finite Time Interval ◽  
Markovian Jumping ◽  
Stochastic Boundedness ◽  
Partly Unknown Transition Probabilities ◽  
Finite Time Boundedness

This paper is concerned with the problem of finite-time boundedness for a class of delayed Markovian jumping neural networks with partly unknown transition probabilities. By introducing the appropriate stochastic Lyapunov-Krasovskii functional and the concept of stochastically finite-time stochastic boundedness for Markovian jumping neural networks, a new method is proposed to guarantee that the state trajectory remains in a bounded region of the state space over a prespecified finite-time interval. Finally, numerical examples are given to illustrate the effectiveness and reduced conservativeness of the proposed results.

Sign in / Sign up

Export Citation Format

Share Document