Extended Dissipative Criteria for Generalized Markovian Jump Neural Networks Including Asynchronous Mode-Dependent Delayed States

2022 ◽  
Author(s):  
Ramasamy Saravanakumar ◽  
M. Syed Ali
Keyword(s):  
Neural Networks ◽  
Asynchronous Mode ◽  
Markovian Jump ◽  
Markovian Jump Neural Networks

Asynchronous finite-time state estimation for semi-Markovian jump neural networks with randomly occurred sensor nonlinearities

2021 ◽  
Vol 432 ◽  
pp. 240-249
Author(s):  
Yao Wang ◽  
Shengyuan Xu ◽  
Yongmin Li ◽  
Yuming Chu ◽  
Zhengqiang Zhang
Keyword(s):  
Neural Networks ◽  
State Estimation ◽  
Finite Time ◽  
Markovian Jump ◽  
Markovian Jump Neural Networks

scholarly journals H∞ Synchronization of Semi-Markovian Jump Neural Networks with Randomly Occurring Time-Varying Delays

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Mengping Xing ◽  
Hao Shen ◽  
Zhen Wang
Keyword(s):  
Neural Networks ◽  
Continuous Time ◽  
Lyapunov Stability Theory ◽  
Schur Complement ◽  
Jensen Inequality ◽  
Time Varying ◽  
Transition Rates ◽  
Markovian Jump ◽  
Synchronization Problem ◽  
Markovian Jump Neural Networks

Based on the Lyapunov stability theory, this paper mainly investigates the H∞ synchronization problem for semi-Markovian jump neural networks (semi-MJNNs) with randomly occurring time-varying delays (TVDs). The continuous-time semi-MJNNs, where the transition rates are dependent on sojourn time, are introduced to make the issue under our consideration more general. One of the main characteristics of our work is the handling of TVDs. In addition to using the improved Jensen inequality and the reciprocal convexity lemma to deal with the integral inequality, we also employ Schur complement and the projection lemma to achieve the decoupling between the square term of TVDs. Finally, we verify the validity and feasibility of our method by a couple of simulation examples.

Sign in / Sign up

Export Citation Format

Share Document