Stochastic stability criteria and event-triggered control of delayed Markovian jump quaternion-valued neural networks
作者：
Highlights：
• The Markov jumps QVNNs is split into four RVNNs, which can be analysed by the analysis method in real number field.
• The event-triggered mechanism introduced into QVNNs, the stochastic stabilization of Markovian jump QVNNs is explored for the first time.
• In order that reducing the conservatism, by constructing a novel augmented LKF containing more hybrid features with respect to the practical sampling pattern with combining some inequality techniques and convex combination optimal skill, a new stabilization condition is derived in the form of LMIs. This makes it easier to verify the results with MATLAB.
摘要
•The Markov jumps QVNNs is split into four RVNNs, which can be analysed by the analysis method in real number field.•The event-triggered mechanism introduced into QVNNs, the stochastic stabilization of Markovian jump QVNNs is explored for the first time.•In order that reducing the conservatism, by constructing a novel augmented LKF containing more hybrid features with respect to the practical sampling pattern with combining some inequality techniques and convex combination optimal skill, a new stabilization condition is derived in the form of LMIs. This makes it easier to verify the results with MATLAB.
论文关键词：Quaternion-valued neural network,Markov jumps,Stochastic stabilization,Event-triggered sampled-data
论文评审过程：Received 13 May 2021, Revised 5 November 2021, Accepted 27 December 2021, Available online 10 January 2022, Version of Record 10 January 2022.
论文官网地址：https://doi.org/10.1016/j.amc.2021.126904
