Finite-time synchronisation of delayed fractional-order coupled neural networks. Issue 12 (10th September 2022)

• Record Type: Journal Article
• Authors: Zhang, Shuailei; Liu, Xinge; Li, Xuemei
• Is Part Of: International journal of systems science. Volume 53:Issue 12(2022)
• Page Start: 2597
• Page End: 2611
• Publication Date: 2022-09-10
• Subjects: Finite-time synchronisation -- fractional order -- Razumikhin-type theorem -- global synchronisation; System analysis -- Periodicals; 003.3
• DOI: 10.1080/00207721.2022.2067910
• Languages: English
• ISSNs: 0020-7721

Abstract

Abstract : This paper considers the global synchronisation and finite-time synchronisation for a class of delayed fractional-order complex neural networks (DFOCNNs). Based on the properties of fractional-order calculus and the Razumikhin-type Lyapunov theorem of a fractional-order system, two new lemmas are proved. These lemmas are employed to formulate a couple of novel criteria for both finite-time synchronisation and global synchronisation of DFOCNNs. Moreover, the upper bound of the setting time for synchronisation is given. Three examples are provided to verify the effectiveness of the obtained results.