Exponential H∞ synchronization and anti-synchronization of delayed discrete-time complex-valued neural networks with uncertainties
Priyanka K.S.R. Soundararajan G. Kashkynbayev A. Nagamani G.
May 2023Elsevier B.V.
Mathematics and Computers in Simulation
2023#207301 - 321 pp.
This paper investigates the problem of exponential synchronization and anti-synchronization for uncertain discrete-time neural networks (NNs) having time-varying delays with H∞ performance in complex domain. An output-feedback controller is utilized not only to guarantee the synchronization criteria between the addressed discrete-time complex-valued neural networks (CVNNs) but also to reduce the effect of external disturbance. In order to assure the anti-synchronization criteria with H∞ performance for the proposed CVNNs, we have introduced the output-feedback controller by anti-synchronization error analysis. With the help of Lyapunov–Krasovskii functional (LKF), some linear matrix inequality (LMI) based sufficient conditions are derived for both synchronization and anti-synchronization criteria which can be validated through YALMIP toolbox in MATLAB software. At last, a numerical simulation result is provided to verify the correctness of the established theoretical results.
Anti-synchronization , Complex-valued neural networks , Linear matrix inequality , Lyapunov–Krasovskii functional , Output-feedback control , Synchronization
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Department of Mathematics, The Gandhigram Rural Institute (Deemed to be University), Tamil Nadu, Gandhigram, 624 302, India
Department of Mathematics, School of Sciences and Humanities, Nazarbayev University, Nur-Sultan, Kazakhstan
Institute of Mathematics and Mathematical Modeling, Almaty, Kazakhstan
Department of Mathematics
Department of Mathematics
Institute of Mathematics and Mathematical Modeling
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