Finite-/fixed-time synchronization of delayed Clifford-valued recurrent neural networks

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Abstract

This paper investigates the problem of finite-/fixed-time synchronization for Clifford-valued recurrent neural networks with time-varying delays. The considered Clifford-valued drive and response system models are firstly decomposed into real-valued drive and response system models in order to overcome the difficulty of the noncommutativity of the multiplication of Clifford numbers. Then, suitable time-delayed feedback controllers are devised to investigate the synchronization problem in finite-/fixed-time of error system. On the basis of new Lyapunov–Krasovskii functional and new computational techniques, finite-/fixed-time synchronization criteria are formulated for the corresponding real-valued drive and response system models. Two numerical examples demonstrate the effectiveness of the theoretical results.

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Boonsatit, N., Rajchakit, G., Sriraman, R., Lim, C. P., & Agarwal, P. (2021). Finite-/fixed-time synchronization of delayed Clifford-valued recurrent neural networks. Advances in Difference Equations, 2021(1). https://doi.org/10.1186/s13662-021-03438-1

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