Stochastic stabilization of Markov jump quaternion-valued neural network using sampled-data control
作者：
Highlights：
• Markov characteristics are introduced into delayed QVNNs for the first time. The existence and uniqueness of the equilibrium point of the Markov jump QVNNs is proved according to the theory of homeomorphism mapping.
• The sampled data controller is firstly proposed for the stochastic stabilization of Markov jump QVNNs.
• A new LKF is constructed for Markov jump QVNNs, which can fully capture the information of sampling, time delay, Markov characteristics and complex valued activation functions.
摘要
•Markov characteristics are introduced into delayed QVNNs for the first time. The existence and uniqueness of the equilibrium point of the Markov jump QVNNs is proved according to the theory of homeomorphism mapping.•The sampled data controller is firstly proposed for the stochastic stabilization of Markov jump QVNNs.•A new LKF is constructed for Markov jump QVNNs, which can fully capture the information of sampling, time delay, Markov characteristics and complex valued activation functions.
论文关键词：Quaternion-valued neural networks,Sampled-data control,Markov jump parameters,Time-varying delay,Stochastic stabilization
论文评审过程：Received 4 February 2020, Revised 13 December 2020, Accepted 31 January 2021, Available online 17 February 2021, Version of Record 17 February 2021.
论文官网地址：https://doi.org/10.1016/j.amc.2021.126041
