Exponential input-to-state stability of quaternion-valued neural networks with time delay

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This paper debated the exponential input-to-state stability (EITSS) of the solution for a kind of quaternion-valued neural networks (QVNNs) with time delay. It fills the blank of QVNN in the aspect of input-to-state stability (ITSS). In virtue of the quaternion multiplication is not suitable for commutative law, QVNN is ordinarily resolved into four real-valued neural networks (RVNNs). Making use of a novel Lyapunov–Krasovskii function and some inequalities, we obtain a little sufficient conditions to assure the considered system is EITSS. Finally, by means of two examples, it is certified that the calculation results in this paper are fine.

论文关键词:Quaternion-valued neural network,Exponential input-to-state stability,Linear matrix inequality

论文评审过程:Received 22 January 2019, Revised 25 March 2019, Accepted 14 April 2019, Available online 6 May 2019, Version of Record 6 May 2019.

论文官网地址:https://doi.org/10.1016/j.amc.2019.04.045