Mutiple ψ-type stability of fractional-order quaternion-valued neural networks
作者：
Highlights：
• In this paper, the problem of multiple ψ-type stability of fractional-order quaternion-valued neural networks was investigated. To the best of our knowledge, this is the first time to discuss the multiple ψ-type stability problem for quaternion networks.
• A quaternion-valued matrix is uniquely decomposed into four real valued matrices and mapped into two similarly sized systems this method will help to avoid many redundant computations.
• Compared with the complex-valued neural networks quaternion valued neural networks have 34n equilibrium points. Among them 24n equilibrium points are exponentially stable.
摘要
•In this paper, the problem of multiple ψ-type stability of fractional-order quaternion-valued neural networks was investigated. To the best of our knowledge, this is the first time to discuss the multiple ψ-type stability problem for quaternion networks.•A quaternion-valued matrix is uniquely decomposed into four real valued matrices and mapped into two similarly sized systems this method will help to avoid many redundant computations.•Compared with the complex-valued neural networks quaternion valued neural networks have 34n equilibrium points. Among them 24n equilibrium points are exponentially stable.
论文关键词：Multiple stability,ψ-type functions,Fractional-order,Quaternion-valued neural networks
论文评审过程：Received 28 September 2020, Revised 2 February 2021, Accepted 4 February 2021, Available online 20 February 2021, Version of Record 20 February 2021.
论文官网地址：https://doi.org/10.1016/j.amc.2021.126092
