Synchronization in Finite-Time Analysis of Clifford-Valued Neural Networks with Finite-Time Distributed Delays

Grienggrai Rajchakit, Ramalingam Sriraman, Chee Peng Lim, Panu Sam-ang and Porpattama Hammachukiattikul
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Grienggrai Rajchakit: Department of Mathematics, Faculty of Science, Maejo University, Chiang Mai 50290, Thailand
Ramalingam Sriraman: Department of Mathematics, Thiruvalluvar University, Vellore 632115, India
Chee Peng Lim: Institute for Intelligent Systems Research and Innovation, Deakin University, Waurn Ponds, VIC 3216, Australia
Panu Sam-ang: School of Mathematics, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand
Porpattama Hammachukiattikul: Department of Mathematics, Faculty of Science and Technology, Phuket Rajabhat University, Phuket 83000, Thailand

Mathematics, 2021, vol. 9, issue 11, 1-18

Abstract: In this paper, we explore the finite-time synchronization of Clifford-valued neural networks with finite-time distributed delays. To address the problem associated with non-commutativity pertaining to the multiplication of Clifford numbers, the original n -dimensional Clifford-valued drive and response systems are firstly decomposed into the corresponding 2 m -dimensional real-valued counterparts. On the basis of a new Lyapunov–Krasovskii functional, suitable controller and new computational techniques, finite-time synchronization criteria are formulated for the corresponding real-valued drive and response systems. The feasibility of the main results is verified by a numerical example.

Keywords: Clifford-valued neural network; finite-time synchronization; distributed delay; Lyapunov–Krasovskii fractional (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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