Global Stabilization of Fuzzy Memristor-Based Reaction-Diffusion Neural Networks
Date of Original Version
This article investigates the global stabilization problem of Takagi-Sugeno fuzzy memristor-based neural networks with reaction-diffusion terms and distributed time-varying delays. By using the Green formula and proposing fuzzy feedback controllers, several algebraic criteria dependent on the diffusion coefficients are established to guarantee the global exponential stability of the addressed networks. Moreover, a simpler stability criterion is obtained by designing an adaptive fuzzy controller. The results derived in this article are generalized and include some existing ones as special cases. Finally, the validity of the theoretical results is verified by two examples.
IEEE Transactions on Cybernetics
Wang, Leimin, Haibo He, Zhigang Zeng, and Cheng Hu. "Global Stabilization of Fuzzy Memristor-Based Reaction-Diffusion Neural Networks." IEEE Transactions on Cybernetics 50, 11 (2020): 4658-4669. doi:10.1109/TCYB.2019.2949468.