Non-fragile dissipative state estimation for semi-Markov jump inertial neural networks with reaction-diffusion

作者：

Highlights：

• As the first attempt, the model of semi-Markov jump inertial neural networks with reaction-diffusion terms are taken into account.

• A mode-dependent state estimator is proposed to overcome the problem of the unmeasurable neuron states.

• The novel structure of transition probability considered in this paper makes the results have higher accuracy and low conservativeness.

摘要

•As the first attempt, the model of semi-Markov jump inertial neural networks with reaction-diffusion terms are taken into account.•A mode-dependent state estimator is proposed to overcome the problem of the unmeasurable neuron states.•The novel structure of transition probability considered in this paper makes the results have higher accuracy and low conservativeness.

论文关键词：Inertial neural networks,Semi-Markov jump systems,Dissipative state estimation,Reaction-diffusion terms,Sojourn-time-dependent transition rate

论文评审过程：Received 20 January 2021, Revised 23 April 2021, Accepted 23 May 2021, Available online 17 July 2021, Version of Record 17 July 2021.

论文官网地址：https://doi.org/10.1016/j.amc.2021.126404