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

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 <i>n</i>-dimensional Clifford-valu...

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Bibliographic Details
Main Authors: Grienggrai Rajchakit, Ramalingam Sriraman, Chee Peng Lim, Panu Sam-ang, Porpattama Hammachukiattikul
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/9/11/1163
Description
Summary: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 <i>n</i>-dimensional Clifford-valued drive and response systems are firstly decomposed into the corresponding <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>2</mn><mi>m</mi></msup></semantics></math></inline-formula>-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.
ISSN:2227-7390