Global Synchronization of Fuzzy Memristive Neural Networks with Discrete and Distributed Delays
Document Type
Article
Date of Original Version
9-1-2020
Abstract
This paper investigates the synchronization problem of Takagi-Sugeno fuzzy memristive neural networks (FMNNs) with mixed delays, in which the bounded distributed and unbounded discrete time-varying delays are involved. Then, under the nonsmooth analysis and Lyapunov stability theory, several easily verified algebraic criteria are established to guarantee the global synchronization of FMNNs via a designed fuzzy feedback controller. Moreover, to show the superiority of the theoretical results, several discussions and comparisons with existing work are provided, indicating that derived results in this paper are general and include several existing ones as special cases. Finally, two numerical examples and two applications in psuedorandom number generation and image encryption are presented to show the validity and practicability of the theoretical results.
Publication Title, e.g., Journal
IEEE Transactions on Fuzzy Systems
Volume
28
Issue
9
Citation/Publisher Attribution
Wang, Leimin, Haibo He, and Zhigang Zeng. "Global Synchronization of Fuzzy Memristive Neural Networks with Discrete and Distributed Delays." IEEE Transactions on Fuzzy Systems 28, 9 (2020): 2022-2034. doi: 10.1109/TFUZZ.2019.2930032.