TY - JOUR
T1 - Finite-Time Dissipative Synchronization for Markovian Jump Generalized Inertial Neural Networks with Reaction-Diffusion Terms
AU - Song, Xiaona
AU - Man, Jingtao
AU - Ahn, Choon Ki
AU - Song, Shuai
N1 - Funding Information:
Manuscript received September 19, 2019; accepted November 23, 2019. Date of publication December 27, 2019; date of current version May 18, 2021. This work was supported in part by the National Natural Science Foundation of China under Grant 61976081 and Grant U1604146, in part by the Foundation for the University Technological Innovative Talents of Henan Province under Grant 18HASTIT019, and in part by the National Research Foundation of Korea through the Ministry of Science, ICT and Future Planning under Grant NRF-2017R1A1A1A05001325. This article was recommended by Associate Editor H. R. Karimi. (Corresponding author: Choon Ki Ahn.) X. Song and J. Man are with the School of Information Engineering, Henan University of Science and Technology, Luoyang 471023, China (e-mail: xiaona_97@163.com; mjt546@163.com).
Publisher Copyright:
© 2013 IEEE.
PY - 2021/6
Y1 - 2021/6
N2 - A novel generalized neural network (NN), which includes Markovian jump parameters, inertial items, and reaction-diffusion terms, is proposed, and the issue of finite-time dissipative synchronization for this kind of NNs is discussed in this article. First, an appropriate variable substitution is employed so that the original second-order differential system is transformed into a first-order one. Second, a novel time-varying memory-based controller is designed to ensure the dissipative synchronization of the drive and response systems over a finite-time interval. Then, a new Lyapunov-Krasovskii function is processed by reciprocally convex combination and free-weighting matrix methods, therefore, a less conservative synchronization criterion is derived. Finally, by providing three examples, the feasibility, superiority, and practicality of the obtained results are illustrated.
AB - A novel generalized neural network (NN), which includes Markovian jump parameters, inertial items, and reaction-diffusion terms, is proposed, and the issue of finite-time dissipative synchronization for this kind of NNs is discussed in this article. First, an appropriate variable substitution is employed so that the original second-order differential system is transformed into a first-order one. Second, a novel time-varying memory-based controller is designed to ensure the dissipative synchronization of the drive and response systems over a finite-time interval. Then, a new Lyapunov-Krasovskii function is processed by reciprocally convex combination and free-weighting matrix methods, therefore, a less conservative synchronization criterion is derived. Finally, by providing three examples, the feasibility, superiority, and practicality of the obtained results are illustrated.
KW - Finite-time dissipative synchronization
KW - Markovian jump parameters
KW - generalized inertial neural networks (GINNs)
KW - reaction-diffusion terms
KW - time-varying memory-based controller
UR - http://www.scopus.com/inward/record.url?scp=85106506921&partnerID=8YFLogxK
U2 - 10.1109/TSMC.2019.2958419
DO - 10.1109/TSMC.2019.2958419
M3 - Article
AN - SCOPUS:85106506921
SN - 1083-4427
VL - 51
SP - 3650
EP - 3661
JO - IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
JF - IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
IS - 6
M1 - 8944299
ER -