Non-fragile finite-time l2-l∞ state estimation for discrete-time Markov jump neural networks with unreliable communication links

@article{Li2015NonfragileFL,
  title={Non-fragile finite-time l2-l∞ state estimation for discrete-time Markov jump neural networks with unreliable communication links},
  author={Feng Li and Hao Shen and Mengshen Chen and Qingkai Kong},
  journal={Applied Mathematics and Computation},
  year={2015},
  volume={271},
  pages={467-481}
}
This paper is concerned with the problem of finite-time l2−l∞ non-fragile state estimation for discrete-time Markov jump neural networks with unreliable communication links. The simultaneous occurrences of packet dropouts, time delays and the sensor nonlinearity stemmed from the unreliable communication links are considered. The focus is on the design of nonfragile state estimator such that the augmented estimation error system is mean-square stochastically finite-time stable with a prescribed… CONTINUE READING

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