Exponential synchronization of memristor-based competitive neural networks with reaction-diffusions and infinite distributed delays

L Wang, CK Zhang - IEEE transactions on neural networks and …, 2022 - ieeexplore.ieee.org
Taking into account the infinite distributed delays and reaction-diffusions, this article
investigates the global exponential synchronization problem of a class of memristor-based …

Fuzzy sampled-data control for synchronization of T–S fuzzy reaction–diffusion neural networks with additive time-varying delays

R Zhang, D Zeng, JH Park, HK Lam… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This article focuses on the exponential synchronization problem of TS fuzzy reaction-
diffusion neural networks (RDNNs) with additive time-varying delays (ATVDs). Two control …

Fuzzy adaptive event-triggered sampled-data control for stabilization of T–S fuzzy memristive neural networks with reaction–diffusion terms

R Zhang, D Zeng, JH Park, HK Lam… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This article focuses on the design of a fuzzy adaptive event-triggered sampled-data control
(AETSDC) scheme for stabilization of Takagi-Sugeno (TS) fuzzy memristive neural networks …

Prefixed-time local intermittent sampling synchronization of stochastic multicoupling delay reaction–diffusion dynamic networks

K Ding, Q Zhu, T Huang - IEEE Transactions on Neural …, 2022 - ieeexplore.ieee.org
This article focuses on the problem of prefixed-time synchronization for stochastic
multicoupled delay dynamic networks with reaction–diffusion terms and discontinuous …

Global Mittag–Leffler stability of the delayed fractional-coupled reaction-diffusion system on networks without strong connectedness

Y Cao, Y Kao, JH Park, H Bao - IEEE Transactions on Neural …, 2021 - ieeexplore.ieee.org
In this article, we mainly consider the existence of solutions and global Mittag–Leffler
stability of delayed fractional-order coupled reaction-diffusion neural networks without strong …

Stability and synchronization of fractional-order reaction–diffusion inertial time-delayed neural networks with parameters perturbation

H Wang, Y Gu, X Zhang, Y Yu - Neural Networks, 2024 - Elsevier
This study is centered around the dynamic behaviors observed in a class of fractional-order
generalized reaction–diffusion inertial neural networks (FGRDINNs) with time delays. These …

Adaptive event-triggered mechanism to synchronization of reaction–diffusion CVNNs and its application in image secure communication

T Wu, J Cao, L **ong, JH Park… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This article is centered on the formulation of a refined adaptive sampled-data-based event-
triggering control (ASDBETC) scheme for the synchronization of reaction–diffusion complex …

Robust H∞ Pinning Synchronization for Multiweighted Coupled Reaction–Diffusion Neural Networks

LH Zhao, S Wen, S Zhu, Z Guo… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This article focuses on the robust synchronization of two types of coupled reaction–diffusion
neural networks with multiple state and spatial diffusion couplings by utilizing pinning …

Quasisynchronization of reaction–diffusion neural networks under deception attacks

R Zhang, H Wang, JH Park, HK Lam… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This study focuses on the quasisynchronization problem for reaction–diffusion neural
networks (RDNNs) in the presence of deception attacks. Under deception attacks, a time …

Synchronization of complex dynamical networks subject to noisy sampling interval and packet loss

Z Hu, H Ren, P Shi - IEEE Transactions on Neural Networks …, 2021 - ieeexplore.ieee.org
This article focuses on the sampled-data synchronization issue for a class of complex
dynamical networks (CDNs) subject to noisy sampling intervals and successive packet …