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

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1163
Author(s):  
Grienggrai Rajchakit ◽  
Ramalingam Sriraman ◽  
Chee Peng Lim ◽  
Panu Sam-ang ◽  
Porpattama Hammachukiattikul

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 2m-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.

2020 ◽  
Vol 416 ◽  
pp. 152-157 ◽  
Author(s):  
Yanjun Liu ◽  
Junjian Huang ◽  
Yu Qin ◽  
Xinbo Yang

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
N. Boonsatit ◽  
R. Sriraman ◽  
T. Rojsiraphisal ◽  
C.P. Lim ◽  
P. Hammachukiattikul ◽  
...  

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1406
Author(s):  
Shuang Wang ◽  
Hai Zhang ◽  
Weiwei Zhang ◽  
Hongmei Zhang

This paper focuses on investigating the finite-time projective synchronization of Caputo type fractional-order complex-valued neural networks with time delay (FOCVNNTD). Based on the properties of fractional calculus and various inequality techniques, by constructing suitable the Lyapunov function and designing two new types controllers, i.e., feedback controller and adaptive controller, two sufficient criteria are derived to ensure the projective finite-time synchronization between drive and response systems, and the synchronization time can effectively be estimated. Finally, two numerical examples are presented to verify the effectiveness and feasibility of the proposed results.


2017 ◽  
Vol 46 (1) ◽  
pp. 271-291 ◽  
Author(s):  
Chao Zhou ◽  
Wanli Zhang ◽  
Xinsong Yang ◽  
Chen Xu ◽  
Jianwen Feng

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